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Facebook Patent | Audio system including for near field and far field enhancement that uses a contact transducer

Patent: Audio system including for near field and far field enhancement that uses a contact transducer

Drawings: Click to check drawins

Publication Number: 20220180885

Publication Date: 20220609

Applicant: Facebook

Abstract

An audio system for near and far field signal enhancement that uses a contact transducer. The audio system includes a microphone array, the contact transducer, and a controller. The microphone array detects sounds from a local area. The sounds from the local area include a voice of a user of the audio system. The contact transducer may be in contact with the head of the user. The contact transducer detects tissue based vibrations that are generated by the user and pass through tissue of the user prior to being detected by the contact transducer. The controller identifies the voice of the user in the detected sounds using the detected tissue based vibrations and a model, and updates a sound filter based on the identified voice of the user. The audio content is modified using the updated sound filter, and is presented by at least one audio system.

Claims

  1. An audio system comprising: a microphone array configured to detect sounds from a local area, the sounds from the local area including a voice of a user of the audio system; a contact transducer configured to detect tissue based vibrations on a portion of a head of the user, the vibrations generated by the user and pass through tissue of the user prior to being detected by the contact transducer; a controller configured to: identify the voice of the user in the detected sounds using the detected tissue based vibrations and a model; and update a sound filter based on the identified voice of the user, wherein audio content is modified using the updated sound filter, and the modified audio content is presented by at least one audio system.

  2. The audio system of claim 1, wherein the audio system is integrated into a headset.

  3. The audio system of claim 2, wherein the contact transducer is configured to sense vibrations of a portion of a nose of the user.

  4. The audio system of claim 1, wherein the tissue based vibrations are caused by the voice of the user, and the updated sound filter enhances the voice of the user, and the controller is further configured to: modify the audio content with the updated filter, wherein the modified audio content enhances the voice of the user; and provide the modified audio content to a second audio system, wherein the second audio system presents the modified audio content.

  5. The audio system of claim 1, wherein the tissue based vibrations are caused by voice of the user, and the updated sound filter enhances the voice of the user, and the controller is further configured to: modify the audio content with the updated filter, wherein the modified audio content enhances the voice of the user; determine that the modified audio content includes a command; and perform an action in accordance with the command.

  6. The audio system of claim 1, wherein the tissue based vibrations are caused by voice of the user, and the controller is further configured to: train an adaptive beamformer using the tissue based vibrations and the sounds from the local area.

  7. The audio system of claim 1, wherein the tissue based vibrations are caused by voice of the user, and the controller is further configured to: determine spectral and spatial correlations between the voice of the user and the sounds from the local area using the tissue based vibrations; and train the learning model using the determined correlations to distinguish between the voice of the user and other sounds from the local area.

  8. The audio system of claim 1, wherein the tissue based vibrations are caused by voice of the user, and the controller is further configured to: determine one or more functions describing the voice within the local area using the tissue based vibrations, wherein the functions are selected from a group comprising: a temporal response of the voice within the local area, a spectral response of the voice within the local area, and a spatial response of the voice within the local area; train the model using the determined one or more functions to distinguish between the voice of the user and other sounds from the local area.

  9. A method comprising: detecting, via a microphone array of an audio system, sounds from a local area, the sounds from the local area including a voice of a user of the audio system; detecting, via a contact transducer, tissue based vibrations on a portion of a head of the user, the vibrations are generated by the user and pass through tissue of the user prior to being detected by the contact transducer; identifying the voice of the user in the detected sounds using the detected tissue based vibrations and a model; and updating a sound filter based on the identified voice of the user, wherein audio content is modified using the updated sound filter, and the modified audio content is presented by at least one audio system.

  10. The method of claim 9, wherein the tissue based vibrations are caused by the voice of the user, and the updated sound filter enhances the voice of the user, and the method further comprises: modifying the audio content with the updated filter, wherein the modified audio content enhances the voice of the user; and providing the modified audio content to a second audio system, wherein the second audio system presents the modified audio content.

  11. The method of claim 9, wherein the tissue based vibrations are caused by voice of the user, and the updated sound filter enhances the voice of the user, and the method further comprises: modifying the audio content with the updated filter, wherein the modified audio content enhances the voice of the user; determining that the modified audio content includes a command; and performing an action in accordance with the command.

  12. The method of claim 9, wherein the tissue based vibrations are caused by voice of the user, and the method further comprises: training an adaptive beamformer using the tissue based vibrations and the sounds from the local area.

  13. The method of claim 9, wherein the tissue based vibrations are caused by voice of the user, and the method further comprising: determining spectral and spatial correlations between the voice of the user and the sounds from the local area using the tissue based vibrations; and training the learning model using the determined correlations to distinguish between the voice of the user and other sounds from the local area.

  14. The method of claim 1, wherein the tissue based vibrations are caused by voice of the user, and the method further comprising: determining one or more functions describing the voice within the local area using the tissue based vibrations, wherein the functions are selected from a group comprising: a temporal response of the voice within the local area, a spectral response of the voice within the local area, and a spatial response of the voice within the local area; training the model using the determined one or more functions to distinguish between the voice of the user and other sounds from the local area.

  15. The method of claim 9, wherein the audio system is integrated into a headset.

  16. The method of claim 15, wherein the contact transducer is configured to be in contact with a portion of a nose of the user.

  17. A non-transitory computer readable medium configured to store program code instructions, when executed by a processor of an audio system, cause the audio system to perform steps comprising: detecting, via a microphone array of an audio system, sounds from a local area, the sounds from the local area including a voice of a user of the audio system; detecting, via a contact transducer, tissue based vibrations on a portion of a head of the user, the vibrations are generated by the user and pass through tissue of the user prior to being detected by the contact transducer; identifying the voice of the user in the detected sounds using the detected tissue based vibrations and a model; and updating a sound filter based on the identified voice of the user, wherein audio content is modified using the updated sound filter, and the modified audio content is presented by at least one audio system.

  18. The computer readable medium of claim 17, wherein the tissue based vibrations are caused by voice of the user, and the program code instructions, when executed by the processor, further cause the processer to perform steps comprising: training an adaptive beamformer using the tissue based vibrations and the sounds from the local area.

  19. The computer readable medium of claim 17, wherein the tissue based vibrations are caused by voice of the user, and the program code instructions, when executed by the processor, further cause the processer to perform steps comprising: determining spectral and spatial correlations between the voice of the user and the sounds from the local area using the tissue based vibrations; and training the learning model using the determined correlations to distinguish between the voice of the user and other sounds from the local area.

  20. The computer readable medium of claim 17, wherein the tissue based vibrations are caused by voice of the user, and the and the program code instructions, when executed by the processor, further cause the processer to perform steps comprising: determining one or more functions describing the voice within the local area using the tissue based vibrations, wherein the functions are selected from a group comprising: a temporal response of the voice within the local area, a spectral response of the voice within the local area, and a spatial response of the voice within the local area; training the model using the determined one or more functions to distinguish between the voice of the user and other sounds from the local area.

Description

FIELD OF THE INVENTION

[0001] This disclosure relates generally to audio systems, and more specifically to an audio system for near field and far field enhancement that uses a contact transducer.

BACKGROUND

[0002] In noisy environments (e.g., loud restaurant), it can be difficult for conventional audio systems to selectively capture sound from a target acoustic source (e.g., talker, user’s own voice, etc.). The selective capture of sound is affected by whether or not the user is speaking. But in noisy environments, the audio system often cannot distinguish between the user speaking and noise from the environment. Conventional audio systems try to mitigate this using voice activity detectors that rely on the temporal and spectral properties of the wearers voice (e.g., being detected via a conventional microphone) being audible over interfering sounds. But, in low acoustic signal-to-noise ratio (SNR) environments (i.e., a noisy environment) this method often fails as the wearers voice is completely masked by noise.

SUMMARY

[0003] An audio system for near and far field signal enhancement that uses one or more contact transducers. The audio system includes a microphone array, the one or more contact transducers, and a controller. In some embodiments, the audio system may be part of a headset. The microphone array detects sounds from a local area. The microphone array is configured to detect sounds from a local area. The sounds from the local area include a voice of a user of the audio system. The one or more contact transducers may be configured to be in direct contact with and/or indirectly (e.g., one or more intermediate materials between the skin of the user and the contact transducer) in contact with a portion of a head of the user (e.g., the nose of the user, the side of the head, etc.). The one or more contact transducers are configured to detect tissue based vibrations that are generated by the user’s voice and pass through tissue of the user. The controller is configured to identify the voice of the user in the detected sounds using the detected tissue based vibrations and a model (e.g., signal processing and/or machine learning model). The controller is configured to update a sound filter based on the identified voice of the user. The audio content is modified using the updated sound filter, and the modified audio content is presented by at least one audio system (e.g., the audio system or some other audio system in the local area).

[0004] In some embodiments a method for near and far field signal enhancement that uses a contact transducer is described. A microphone array of an audio system detects sounds from a local area. The sounds from the local area include a voice of a user of the audio system. The contact transducer in contact with a portion of a head of the user detects tissue based vibrations that are generated by the user and pass through tissue of the user prior to being detected by the contact transducer. The voice of the user in the detected sounds is identified using the detected tissue based vibrations and a model (e.g., signal processing and/or machine learning model). A sound filter is updated based on the identified voice of the user. The audio content is modified using the updated sound filter, and the modified audio content is presented by at least one audio system.

[0005] In some embodiments, a non-transitory computer readable medium configured to store program code instructions is described. The instructions when executed by a processor of an audio system, cause the audio system to perform steps of the method described above.

BRIEF DESCRIPTION OF THE DRAWINGS

[0006] FIG. 1A is a perspective view of a headset implemented as an eyewear device that includes at least one contact transducer, in accordance with one or more embodiments.

[0007] FIG. 1B is a perspective view of a headset implemented as a head-mounted display that includes at least one contact transducer, in accordance with one or more embodiments.

[0008] FIG. 2 is a block diagram of an audio system, in accordance with one or more embodiments.

[0009] FIG. 3 is a flowchart illustrating a process for near and far field signal enhancement via an audio system that uses a contact transducer, in accordance with one or more embodiments.

[0010] FIG. 4 is a system that includes a headset, in accordance with one or more embodiments.

[0011] The figures depict various embodiments for purposes of illustration only. One skilled in the art will readily recognize from the following discussion that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles described herein.

DETAILED DESCRIPTION

[0012] An audio system for near and far field signal enhancement that uses a contact transducer. As described herein, the near field refers to a region of space relatively close (e.g., the voice of the user, within 30 cm of the audio system, etc.) to the audio system where sound can occur. An example of sound in the near field is a voice of a user of the audio system. Far field refers is a region of space outside of the near field where sound can occur (e.g., a location of a person speaking to the user). The audio system may use sounds from the far field in, e.g., beamforming, speech enhancement, automatic speech recognition, etc. In some instances it may be useful to be able to identify one or more sound sources in the near field, the far field, or both. For example, enhancing a user’s voice in an audio system in a noisy environment. The audio system described herein may be used for near field signal enhancement, far field signal enhancement, or both. The audio system includes a microphone array, one or more contact transducers, and a controller. In some embodiments, the audio system may be part of a headset.

[0013] The microphone array detects sounds from a local area. The microphone array is configured to detect sounds from the local area. The sounds from the local area may include, e.g., a voice of a user of the audio system, sounds from other sound sources in the local area, or some combination thereof.

[0014] The one or more contact transducers detects tissue based vibrations resulting from speech of the user. The one or more contact transducers may be in contact with a portion of a head of the user (e.g., the nose of the user, the side of the head, etc.). When the user speaks, a portion of the speech actually transmits through tissue of the user via tissue conduction. This portion of speech manifests on the skin of the user’s head as slight tissue based vibrations. The one or more contact transducers detect these tissue based vibrations.

[0015] The controller is configured to identify the voice of the user in the detected sounds using the detected tissue based vibrations and a signal processing and/or machine learning model. The controller is configured to update a sound filter based on the identified voice of the user. The audio content is modified using the updated sound filter. The modified audio content may be presented by at least one audio system (e.g., the audio system or some other audio system in the local area). For example, the audio system may enhance the user’s voice in the modified audio content and transmit the modified audio content to another audio system.

[0016] The controller may use the detected tissue vibrations (i.e., output signal) and the detected sounds in a number of ways. The output signals from the one or more contact transducers may be used as a voice activity detector (VAD) for training an adaptive beamformer. The trained adaptive beamformer may be able to better distinguish between different sounds from different sound sources in a local area. In another example, the controller may determine spectral and spatial correlations of the voice of the user and the sounds from the local area using the tissue based vibrations. The controller may train the signal processing and/or machine learning model using the determined spectral and spatial correlations to distinguish the voice of the user from other sounds in the local area. In another example, the controller may determine one or more functions (e.g., temporal response, spectral response, spatial response) describing the user’s voice within the local area using the tissue based vibrations. The controller can train the signal processing and/or machine learning model using the determined one or more functions to distinguish between the user’s voice and other interfering sounds within the local area.

[0017] Conventional VADs do not function well in low acoustic SNR environments (e.g., a crowded restaurant that is noisy). These systems detect sound from the local using a microphone and then try to isolate the user’s voice from within the low acoustic SNR environment. But, in low acoustic SNR environments this method often fails as the wearers voice is completely masked or corrupted by other sounds (e.g., other people speaking in the crowded restaurant). In contrast, the audio system described herein uses contact transducers in direct and/or indirect contact with the skin of the user to detect tissue based signals caused by the user’s voice. The noise in the detected signal is much lower than conventional signals, and it allows for reliable identification of when a user is speaking. Moreover, in some embodiments, the audio system may selectively activate and use the one or more contact based transducers based on am ambient noise level exceeding some threshold value.

[0018] Embodiments of the invention may include or be implemented in conjunction with an artificial reality system. Artificial reality is a form of reality that has been adjusted in some manner before presentation to a user, which may include, e.g., a virtual reality (VR), an augmented reality (AR), a mixed reality (MR), a hybrid reality, or some combination and/or derivatives thereof. Artificial reality content may include completely generated content or generated content combined with captured (e.g., real-world) content. The artificial reality content may include video, audio, haptic feedback, or some combination thereof, any of which may be presented in a single channel or in multiple channels (such as stereo video that produces a three-dimensional effect to the viewer). Additionally, in some embodiments, artificial reality may also be associated with applications, products, accessories, services, or some combination thereof, that are used to create content in an artificial reality and/or are otherwise used in an artificial reality. The artificial reality system that provides the artificial reality content may be implemented on various platforms, including a wearable device (e.g., headset) connected to a host computer system, a standalone wearable device (e.g., headset), a mobile device or computing system, or any other hardware platform capable of providing artificial reality content to one or more viewers.

[0019] FIG. 1A is a perspective view of a headset 100 implemented as an eyewear device, in accordance with one or more embodiments. In some embodiments, the eyewear device is a near eye display (NED). In general, the headset 100 may be worn on the face of a user such that content (e.g., media content) is presented using a display assembly and/or an audio system. However, the headset 100 may also be used such that media content is presented to a user in a different manner. Examples of media content presented by the headset 100 include one or more images, video, audio, or some combination thereof. The headset 100 includes a frame, and may include, among other components, a display assembly including one or more display elements 120, a depth camera assembly (DCA), an audio system, and a position sensor 190. While FIG. 1A illustrates the components of the headset 100 in example locations on the headset 100, the components may be located elsewhere on the headset 100, on a peripheral device paired with the headset 100, or some combination thereof. Similarly, there may be more or fewer components on the headset 100 than what is shown in FIG. 1A.

[0020] The frame 110 holds the other components of the headset 100. The frame 110 includes a front part that holds the one or more display elements 120 and end pieces (e.g., temples) to attach to a head of the user. The front part of the frame 110 bridges the top of a nose of the user. The length of the end pieces may be adjustable (e.g., adjustable temple length) to fit different users. The end pieces may also include a portion that curls behind the ear of the user (e.g., temple tip, ear piece).

[0021] The one or more display elements 120 provide light to a user wearing the headset 100. As illustrated the headset includes a display element 120 for each eye of a user. In some embodiments, a display element 120 generates image light that is provided to an eyebox of the headset 100. The eyebox is a location in space that an eye of user occupies while wearing the headset 100. For example, a display element 120 may be a waveguide display. A waveguide display includes a light source (e.g., a two-dimensional source, one or more line sources, one or more point sources, etc.) and one or more waveguides. Light from the light source is in-coupled into the one or more waveguides which outputs the light in a manner such that there is pupil replication in an eyebox of the headset 100. In-coupling and/or outcoupling of light from the one or more waveguides may be done using one or more diffraction gratings. In some embodiments, the waveguide display includes a scanning element (e.g., waveguide, mirror, etc.) that scans light from the light source as it is in-coupled into the one or more waveguides. Note that in some embodiments, one or both of the display elements 120 are opaque and do not transmit light from a local area around the headset 100. The local area is the area surrounding the headset 100. For example, the local area may be a room that a user wearing the headset 100 is inside, or the user wearing the headset 100 may be outside and the local area is an outside area. In this context, the headset 100 generates VR content. Alternatively, in some embodiments, one or both of the display elements 120 are at least partially transparent, such that light from the local area may be combined with light from the one or more display elements to produce AR and/or MR content.

[0022] In some embodiments, a display element 120 does not generate image light, and instead is a lens that transmits light from the local area to the eyebox. For example, one or both of the display elements 120 may be a lens without correction (non-prescription) or a prescription lens (e.g., single vision, bifocal and trifocal, or progressive) to help correct for defects in a user’s eyesight. In some embodiments, the display element 120 may be polarized and/or tinted to protect the user’s eyes from the sun.

[0023] In some embodiments, the display element 120 may include an additional optics block (not shown). The optics block may include one or more optical elements (e.g., lens, Fresnel lens, etc.) that direct light from the display element 120 to the eyebox. The optics block may, e.g., correct for aberrations in some or all of the image content, magnify some or all of the image, or some combination thereof.

[0024] The DCA determines depth information for a portion of a local area surrounding the headset 100. The DCA includes one or more imaging devices 130 and a DCA controller (not shown in FIG. 1A), and may also include an illuminator 140. In some embodiments, the illuminator 140 illuminates a portion of the local area with light. The light may be, e.g., structured light (e.g., dot pattern, bars, etc.) in the infrared (IR), IR flash for time-of-flight, etc. In some embodiments, the one or more imaging devices 130 capture images of the portion of the local area that include the light from the illuminator 140. As illustrated, FIG. 1A shows a single illuminator 140 and two imaging devices 130. In alternate embodiments, there is no illuminator 140 and at least two imaging devices 130.

[0025] The DCA controller computes depth information for the portion of the local area using the captured images and one or more depth determination techniques. The depth determination technique may be, e.g., direct time-of-flight (ToF) depth sensing, indirect ToF depth sensing, structured light, passive stereo analysis, active stereo analysis (uses texture added to the scene by light from the illuminator 140), some other technique to determine depth of a scene, or some combination thereof.

[0026] The audio system provides audio content. The audio system includes a transducer array, a sensor array, one or more contact transducers 145, and an audio controller 150. However, in other embodiments, the audio system may include different and/or additional components. Similarly, in some cases, functionality described with reference to the components of the audio system can be distributed among the components in a different manner than is described here. For example, some or all of the functions of the controller may be performed by a remote server.

[0027] The transducer array presents sound to user. The transducer array includes a plurality of transducers. A transducer may be a speaker 160 or a tissue transducer 170 (e.g., a bone conduction transducer or a cartilage conduction transducer). Although the speakers 160 are shown exterior to the frame 110, the speakers 160 may be enclosed in the frame 110. In some embodiments, instead of individual speakers for each ear, the headset 100 includes a speaker array comprising multiple speakers integrated into the frame 110 to improve directionality of presented audio content. The tissue transducer 170 couples to the head of the user and directly vibrates tissue (e.g., bone or cartilage) of the user to generate sound. The number and/or locations of transducers may be different from what is shown in FIG. 1A.

[0028] The sensor array detects sounds within the local area of the headset 100. The sensor array includes a plurality of acoustic sensors 180. An acoustic sensor 180 captures sounds emitted from one or more sound sources in the local area (e.g., a room). Each acoustic sensor is configured to detect sound and convert the detected sound into an electronic format (analog or digital). The acoustic sensors 180 may be acoustic wave sensors, microphones, sound transducers, or similar sensors that are suitable for detecting sounds.

[0029] In some embodiments, one or more acoustic sensors 180 may be placed in an ear canal of each ear (e.g., acting as binaural microphones). In some embodiments, the acoustic sensors 180 may be placed on an exterior surface of the headset 100, placed on an interior surface of the headset 100, separate from the headset 100 (e.g., part of some other device), or some combination thereof. The number and/or locations of acoustic sensors 180 may be different from what is shown in FIG. 1A. For example, the number of acoustic detection locations may be increased to increase the amount of audio information collected and the sensitivity and/or accuracy of the information. The acoustic detection locations may be oriented such that the microphone is able to detect sounds in a wide range of directions surrounding the user wearing the headset 100.

[0030] The one or more contact transducers 145 detect tissue based vibrations resulting from speech of the user. A contact transducer 145 may be, e.g., a vibrometer, a contact microphone, an accelerometer, some other transducer that is configured to measure vibration through a surface, or some combination thereof. The one or more contact transducers 145 may be configured to be in contact with one or more portions of a head of the user. In the example shown in FIG. 1A, the contact transducer 145 is located in an area of the frame 110 that would be directly in contact with (the contact transducer 145 is directly touching the skin) and/or indirectly in contact (the contact transducer 145 is separated from the skin by one or more intermediate materials that transmit vibrations of the skin to the contact transducer 145) with a portion of a nose of a user wearing the headset 100. For example, it could be integrated into one or both nose pads of a set of glasses. In other embodiments, the contact transducer 145 may be located elsewhere on the headset 100 and/or there may be one or more additional contact transducers 145 on the headset 100 (e.g., could have one on each nose pad). When the user speaks, a portion of the speech actually transmits through tissue of the user via tissue conduction. This portion of speech manifests on the skin of the user’s head as slight tissue based vibrations. The one or more contact transducers 145 detect these tissue based vibrations.

[0031] The audio controller 150 processes the detected tissue vibrations and information from the sensor array that describes sounds detected by the sensor array. The audio controller 150 may comprise a processor and a computer-readable storage medium. The audio controller 150 may be configured to generate direction of arrival (DOA) estimates, generate acoustic transfer functions (e.g., array transfer functions and/or head-related transfer functions), track the location of sound sources, form beams in the direction of sound sources, classify sound sources, generate sound filters for the speakers 160, train and/or use a signal processing and/or machine learning model, or some combination thereof. Moreover, in some embodiments, the audio controller 150 may selectively activate and use the one or more contact based transducers 145 based on am ambient noise level exceeding some threshold value. Additional details regarding how the audio controller 150 may use the detected tissue vibrations are described below in detail with regard to FIGS. 2 and 3.

[0032] The position sensor 190 generates one or more measurement signals in response to motion of the headset 100. The position sensor 190 may be located on a portion of the frame 110 of the headset 100. The position sensor 190 may include an inertial measurement unit (IMU). Examples of position sensor 190 include: one or more accelerometers, one or more gyroscopes, one or more magnetometers, another suitable type of sensor that detects motion, a type of sensor used for error correction of the IMU, or some combination thereof. The position sensor 190 may be located external to the IMU, internal to the IMU, or some combination thereof.

[0033] In some embodiments, the headset 100 may provide for simultaneous localization and mapping (SLAM) for a position of the headset 100 and updating of a model of the local area. For example, the headset 100 may include a passive camera assembly (PCA) that generates color image data. The PCA may include one or more RGB cameras that detect images of some or all of the local area. In some embodiments, some or all of the imaging devices 130 of the DCA may also function as the PCA. The images detected by the PCA and the depth information determined by the DCA may be used to determine parameters of the local area, generate a model of the local area, update a model of the local area, or some combination thereof. Furthermore, the position sensor 190 tracks the position (e.g., location and pose) of the headset 100 within the room. Additional details regarding the components of the headset 100 are discussed below in connection with FIG. 4.

[0034] FIG. 1B is a perspective view of a headset 105 implemented as a HMD, in accordance with one or more embodiments. In embodiments that describe an AR system and/or a MR system, portions of a front side of the HMD are at least partially transparent in the visible band (.about.380 nm to 750 nm), and portions of the HMD that are between the front side of the HMD and an eye of the user are at least partially transparent (e.g., a partially transparent electronic display). The HMD includes a front rigid body 115 and a band 175. The headset 105 includes many of the same components described above with reference to FIG. 1A, but modified to integrate with the HMD form factor. For example, the HMD includes a display assembly, a DCA, an audio system (that includes one or more contact transducers 145), and a position sensor 190. FIG. 1B shows the illuminator 140, a plurality of the speakers 160, a plurality of the imaging devices 130, a plurality of acoustic sensors 180, and the position sensor 190. The speakers 160 may be located in various locations, such as coupled to the band 175 (as shown), coupled to front rigid body 115, or may be configured to be inserted within the ear canal of a user.

[0035] FIG. 2 is a block diagram of an audio system 200, in accordance with one or more embodiments. The audio system in FIG. 1A or FIG. 1B may be an embodiment of the audio system 200. The audio system 200 generates one or more acoustic transfer functions for a user. The audio system 200 may then use the one or more acoustic transfer functions to generate audio content for the user. In the embodiment of FIG. 2, the audio system 200 includes a transducer array 210, a sensor array 220, one or more contact transducers 145, and an audio controller 230. Some embodiments of the audio system 200 have different components than those described here. Similarly, in some cases, functions can be distributed among the components in a different manner than is described here.

[0036] The transducer array 210 is configured to present audio content. The transducer array 210 includes a plurality of transducers. A transducer is a device that provides audio content. A transducer may be, e.g., a speaker (e.g., the speaker 160), a tissue transducer (e.g., the tissue transducer 170), some other device that provides audio content, or some combination thereof. A tissue transducer may be configured to function as a bone conduction transducer or a cartilage conduction transducer. The transducer array 210 may present audio content via air conduction (e.g., via one or more speakers), via bone conduction (via one or more bone conduction transducer), via cartilage conduction audio system (via one or more cartilage conduction transducers), or some combination thereof. In some embodiments, the transducer array 210 may include one or more transducers to cover different parts of a frequency range. For example, a piezoelectric transducer may be used to cover a first part of a frequency range and a moving coil transducer may be used to cover a second part of a frequency range.

[0037] The bone conduction transducers generate acoustic pressure waves by vibrating bone/tissue in the user’s head. A bone conduction transducer may be coupled to a portion of a headset, and may be configured to be behind the auricle coupled to a portion of the user’s skull. The bone conduction transducer receives vibration instructions from the audio controller 230, and vibrates a portion of the user’s skull based on the received instructions. The vibrations from the bone conduction transducer generate a tissue-borne acoustic pressure wave that propagates toward the user’s cochlea, bypassing the eardrum.

[0038] The cartilage conduction transducers generate acoustic pressure waves by vibrating one or more portions of the auricular cartilage of the ears of the user. A cartilage conduction transducer may be coupled to a portion of a headset, and may be configured to be coupled to one or more portions of the auricular cartilage of the ear. For example, the cartilage conduction transducer may couple to the back of an auricle of the ear of the user. The cartilage conduction transducer may be located anywhere along the auricular cartilage around the outer ear (e.g., the pinna, the tragus, some other portion of the auricular cartilage, or some combination thereof). Vibrating the one or more portions of auricular cartilage may generate: airborne acoustic pressure waves outside the ear canal; tissue born acoustic pressure waves that cause some portions of the ear canal to vibrate thereby generating an airborne acoustic pressure wave within the ear canal; or some combination thereof. The generated airborne acoustic pressure waves propagate down the ear canal toward the ear drum.

[0039] The transducer array 210 generates audio content in accordance with instructions from the audio controller 230. In some embodiments, the audio content is spatialized. Spatialized audio content is audio content that appears to originate from a particular direction and/or target region (e.g., an object in the local area and/or a virtual object). For example, spatialized audio content can make it appear that sound is originating from a virtual singer across a room from a user of the audio system 200. The transducer array 210 may be coupled to a wearable device (e.g., the headset 100 or the headset 105). In alternate embodiments, the transducer array 210 may be a plurality of speakers that are separate from the wearable device (e.g., coupled to an external console).

[0040] The sensor array 220 detects sounds within a local area surrounding the sensor array 220. The detected sounds may be, e.g., from the user of the audio system 200 (e.g., the user’s voice) and/or sounds from other sound sources (e.g., other people) in the local area. The sensor array 220 may include a plurality of acoustic sensors that each detect air pressure variations of a sound wave and convert the detected sounds into an electronic format (analog or digital). The plurality of acoustic sensors may be positioned on a headset (e.g., headset 100 and/or the headset 105), on a user (e.g., in an ear canal of the user), on a neckband, or some combination thereof. An acoustic sensor may be, e.g., a microphone, a vibration sensor, an accelerometer, or any combination thereof. In some embodiments, the sensor array 220 is configured to monitor the audio content generated by the transducer array 210 using at least some of the plurality of acoustic sensors. Increasing the number of sensors may improve the accuracy of information (e.g., directionality) describing a sound field produced by the transducer array 210 and/or sound from the local area.

[0041] The one or more contact transducers 145 detect tissue based vibrations resulting from speech of the user. When the user speaks in addition to air based pressure waves there are tissue based pressure waves that are produced. And a portion of these tissue based pressure waves (caused by the user’s speech) transmits through tissue of the user via tissue conduction and manifests on the skin of the user’s head as tissue based vibrations. The one or more contact transducers 145 are in contact with the skin of the user’s head, and detect these tissue based vibrations. The contact transducer 145 may be, e.g., a vibrometer, a contact microphone, some other transducer that is configured to measure vibration through a surface, or some combination thereof. The one or more contact transducers 145 are configured to be in contact with one or more portions of a head of the user.

[0042] In the example shown in FIG. 1A, the contact transducer 145 is located in an area of the frame 110 that would be in contact with a portion of a nose of a user wearing the headset 100. For example, it could be integrated into one or both nose pads of a set of glasses. In other embodiments, the contact transducer 145 may be located elsewhere on the headset 100 and/or there may be one or more additional contact transducers 145 on the headset 100 (e.g., could have one on each nose pad). For example, the contact transducer 145 may be located on the headset anywhere that would come into contact with the head of the user.

[0043] The audio controller 230 controls operation of the audio system 200. In the embodiment of FIG. 2, the audio controller 230 includes a data store 235, a DOA estimation module 240, a transfer function module 250, a tracking module 260, a beamforming module 270, a voice activity detection (VAD) module 275, and a sound filter module 280. The audio controller 230 may be located inside a headset, in some embodiments. Some embodiments of the audio controller 230 have different components than those described here. Similarly, functions can be distributed among the components in different manners than described here. For example, some functions of the controller may be performed external to the headset. The user may opt in to allow the audio controller 230 to transmit data detected by the headset to systems external to the headset, and the user may select privacy settings controlling access to any such data.

[0044] The data store 235 stores data for use by the audio system 200. Data in the data store 235 may include sounds recorded in the local area of the audio system 200, audio content, head-related transfer functions (HRTFs), transfer functions for one or more sensors, array transfer functions (ATFs) for one or more of the acoustic sensors, sound source locations, virtual model of local area, direction of arrival estimates, sound filters, tissue vibrations detected by the one or more contact transducers 145, sounds detected by the sensor array 220, and other data relevant for use by the audio system 200, or any combination thereof.

[0045] The user may opt-in to allow the data store 235 to record data detected by the sensor array 220 and/or the one or more contact transducers 145. In some embodiments, the audio system 200 may employ always on recording, in which the audio system 200 records all sounds detected by the sensor array 220 and/or the one or more contact transducers 145. The user may opt in or opt out to allow or prevent the audio system 200 from recording, storing, or transmitting the recorded data to other entities.

[0046] The DOA estimation module 240 is configured to localize sound sources in the local area based in part on information from the sensor array 220. Localization is a process of determining where sound sources are located relative to the user of the audio system 200. The DOA estimation module 240 performs a DOA analysis to localize one or more sound sources within the local area. The DOA analysis may include analyzing the intensity, spectra, and/or arrival time of each sound at the sensor array 220 to determine the direction from which the sounds originated. In some cases, the DOA analysis may include any suitable algorithm for analyzing a surrounding acoustic environment in which the audio system 200 is located.

[0047] For example, the DOA analysis may be designed to receive input signals from the sensor array 220 and apply digital signal processing algorithms to the input signals to estimate a direction of arrival. These algorithms may include, for example, delay and sum algorithms where the input signal is sampled, and the resulting weighted and delayed versions of the sampled signal are averaged together to determine a DOA. A least mean squared (LMS) algorithm may also be implemented to create an adaptive filter. This adaptive filter may then be used to identify differences in signal intensity, for example, or differences in time of arrival. These differences may then be used to estimate the DOA. In another embodiment, the DOA may be determined by converting the input signals into the frequency domain and selecting specific bins within the time-frequency (TF) domain to process. Each selected TF bin may be processed to determine whether that bin includes a portion of the audio spectrum with a direct path audio signal. Those bins having a portion of the direct-path signal may then be analyzed to identify the angle at which the sensor array 220 received the direct-path audio signal. The determined angle may then be used to identify the DOA for the received input signal. Other algorithms not listed above may also be used alone or in combination with the above algorithms to determine DOA.

[0048] In some embodiments, the DOA estimation module 240 may also determine the DOA with respect to an absolute position of the audio system 200 within the local area. The position of the sensor array 220 may be received from an external system (e.g., some other component of a headset, an artificial reality console, a mapping server, a position sensor (e.g., the position sensor 190), etc.). The external system may create a virtual model of the local area, in which the local area and the position of the audio system 200 are mapped. The received position information may include a location and/or an orientation of some or all of the audio system 200 (e.g., of the sensor array 220). The DOA estimation module 240 may update the estimated DOA based on the received position information.

[0049] The transfer function module 250 is configured to generate one or more acoustic transfer functions. Generally, a transfer function is a mathematical function giving a corresponding output value for each possible input value. Based on parameters of the detected sounds, the transfer function module 250 generates one or more acoustic transfer functions associated with the audio system. The acoustic transfer functions may be array transfer functions (ATFs), head-related transfer functions (HRTFs), other types of acoustic transfer functions, or some combination thereof. An ATF characterizes how the microphone receives a sound from a point in space.

[0050] An ATF includes a number of transfer functions that characterize a relationship between the sound source and the corresponding sound received by the acoustic sensors in the sensor array 220. Accordingly, for a sound source there is a corresponding transfer function for each of the acoustic sensors in the sensor array 220. And collectively the set of transfer functions is referred to as an ATF. Accordingly, for each sound source there is a corresponding ATF. Note that the sound source may be, e.g., someone or something generating sound in the local area, the user, or one or more transducers of the transducer array 210. The ATF for a particular sound source location relative to the sensor array 220 may differ from user to user due to a person’s anatomy (e.g., ear shape, shoulders, etc.) that affects the sound as it travels to the person’s ears. Accordingly, the ATFs of the sensor array 220 are personalized for each user of the audio system 200.

[0051] In some embodiments, the transfer function module 250 determines one or more HRTFs for a user of the audio system 200. The HRTF characterizes how an ear receives a sound from a point in space. The HRTF for a particular source location relative to a person is unique to each ear of the person (and is unique to the person) due to the person’s anatomy (e.g., ear shape, shoulders, etc.) that affects the sound as it travels to the person’s ears. In some embodiments, the transfer function module 250 may determine HRTFs for the user using a calibration process. In some embodiments, the transfer function module 250 may provide information about the user to a remote system. The user may adjust privacy settings to allow or prevent the transfer function module 250 from providing the information about the user to any remote systems. The remote system determines a set of HRTFs that are customized to the user using, e.g., machine learning, and provides the customized set of HRTFs to the audio system 200.

[0052] The tracking module 260 is configured to track locations of one or more sound sources. The tracking module 260 may compare current DOA estimates and compare them with a stored history of previous DOA estimates. In some embodiments, the audio system 200 may recalculate DOA estimates on a periodic schedule, such as once per second, or once per millisecond. The tracking module may compare the current DOA estimates with previous DOA estimates, and in response to a change in a DOA estimate for a sound source, the tracking module 260 may determine that the sound source moved. In some embodiments, the tracking module 260 may detect a change in location based on visual information received from the headset or some other external source. The tracking module 260 may track the movement of one or more sound sources over time. The tracking module 260 may store values for a number of sound sources and a location of each sound source at each point in time. In response to a change in a value of the number or locations of the sound sources, the tracking module 260 may determine that a sound source moved. The tracking module 260 may calculate an estimate of the localization variance. The localization variance may be used as a confidence level for each determination of a change in movement.

[0053] The beamforming module 270 is configured to process one or more ATFs to selectively emphasize sounds from sound sources within a certain area while de-emphasizing sounds from other areas thereby functioning as an adaptive beamformer. In analyzing sounds detected by the sensor array 220, the beamforming module 270 may combine information from different acoustic sensors to emphasize sound associated from a particular region of the local area while deemphasizing sound that is from outside of the region. The beamforming module 270 may isolate an audio signal associated with sound from a particular sound source from other sound sources in the local area based on, e.g., different DOA estimates from the DOA estimation module 240 and the tracking module 260. The beamforming module 270 may thus selectively analyze discrete sound sources in the local area. In some embodiments, the beamforming module 270 may enhance a signal from a sound source. For example, the beamforming module 270 may apply sound filters which eliminate signals above, below, or between certain frequencies. Signal enhancement acts to enhance sounds associated with a given identified sound source relative to other sounds detected by the sensor array 220.

[0054] The VAD module 275 determines whether the user is speaking based on output signals output from the one or more contact transducers 145 caused by vibration of the skin of the user. The VAD module 275 may determine whether the user is speaking based on, e.g., frequencies of the detected vibrations, amplitude of the detected vibrations, or both. For example, the VAD module 275 may suppress frequencies outside a range of human voices. The VAD module 275 may also filter out signals corresponding to vibrations lower than a threshold values (e.g., vibrations caused by a person speaking to the user have a lower amplitude than vibrations caused by the user speaking).

[0055] The VAD module 275 may identify the voice of the user in the detected sounds using the detected tissue based vibrations and a signal processing and/or machine learning model. In some embodiments, the signal processing and/or machine learning model is trained using output signals from the one or more contact transducers 145 and sounds detected from the local area. The output signals are tissue based vibrations that occur on the skin of the user when the user speaks. As such, the VAD module 275 can input the output signals from the one or more contact transducers and the sounds from the local area into the signal processing and/or machine learning model which uses the inputs to identify the voice of the user in the detected sounds from the local area. Moreover, the signal processing and/or machine learning model is able to reliably and consistently do so using the inputs in low acoustic SNR environments.

[0056] In some embodiments, VAD 275 may determine that the identified voice of the user includes a command. And the audio system 200 and/or the headset 100 may then perform an action in accordance with the command. The action may control some operation of the audio system 200 and/or the headset 100. An action may, e.g., designate a sound source, decrease/increase volume, some other action that controls an operation of the audio system 200 and/or the headset 100 or some combination thereof.

[0057] The VAD module 275 uses the detected tissue vibrations (i.e., output signal) and the detected sounds in a number of ways. In some embodiments, the VAD module 275 trains the beamforming module 270 using output signals from the one or more contact transducers 145. The VAD module 275 can directly inform the beamforming module 270 how to adapt by letting it know when the near-field vs far-field is active (it is generally assumed that near-field signals are primarily the same signal that the contact microphone picks up and that near and far field are spatial definitions). An estimated users voice activity is used to train the beamforming module 270 to learn at any given time the spatial correlation between the sensors and associate them with the users voice or with an “everything else” signal. By classifying the spatial correlations more accurately using the contact transducer 145 the audio controller 230 can adapt to a more confident and higher performing beamformer (i.e., the beamforming module 270) that either keeps or removes the users voice depending on the application. For example, the audio controller 230 may keep the users voice and remove noise if the user was on a phone call with someone else remote, or may try reduce a level of the user’s voice if the user was conversing with someone in the far-field and the system was enhancing the far field voice, otherwise the user could potentially hear themselves amplified and echoed/feedback. The trained beamforming module (i.e., trained adaptive beamformer) may be able to better distinguish between different sounds from different sound sources in a local area.

[0058] The VAD module 275 may determine one or more functions describing the voice within the local area using the tissue based vibrations. The one or more functions may be, e.g., a temporal response of the voice within the local area, a spectral response of the voice within the local area, a spatial response of the voice within the local area, or some combination thereof. For example, the VAD module 275 may determine spectral and spatial correlations of the voice of the user and the sounds from the local area using the tissue based vibrations. The VAD module 275 may train the signal processing and/or machine learning model using the determined spectral and spatial correlations to distinguish the voice of the user from other sounds in the local area.

[0059] In another example, the VAD module 275 may determine, using the tissue based vibrations and sounds detected from the local area, a temporal response, a spectral response, and a spatial response that describe the user’s voice within the local area. The VAD module 275 can train the signal processing and/or machine learning model using the determined one or more functions to distinguish between the user’s voice and other interfering sounds within the local area.

[0060] The sound filter module 280 determines sound filters for the transducer array 210. In some embodiments, the sound filters cause the audio content to be spatialized, such that the audio content appears to originate from a target region. In some embodiments, the sound filters may cause positive or negative amplification of sounds as a function of frequency. The sound filter module 280 may use HRTFs and/or acoustic parameters to generate the sound filters. The acoustic parameters describe acoustic properties of the local area. The acoustic parameters may include, e.g., a reverberation time, a reverberation level, a room impulse response, etc. In some embodiments, the sound filter module 280 calculates one or more of the acoustic parameters. In some embodiments, the sound filter module 280 requests the acoustic parameters from a mapping server (e.g., as described below with regard to FIG. 4).

[0061] The sound filter module 280 may update one or more sound filters based on the identified voice of the user in the detected sounds. The one or more updated sound filters may be applied to audio content to generate modified audio content. For example, the sound filter module 280 may update a sound filter such that as applied to the audio content, the modified audio content would enhance the identified voice of the user. In another example, the sound filter module 280 may update a sound filter such that as applied to the audio content, the modified audio content would keep the user’s voice and remove noise if the user was on a phone call with someone else remote, reduce a level of the user’s voice if the user was conversing with someone in the far-field and the system was enhancing the far field voice (otherwise the user could potentially hear themselves amplified and echoed/feedback). In some embodiments, the sound filter module 280 provides the sound filters and/or modified audio content to the transducer array 210 and/or one or more other audio systems in the local area. The sound filter module 280 may provide the one or more updated sound filters and/or modified audio content to the one or more other audio systems via, e.g., a local wireless network (e.g., WIFI, BLUETOOTH, etc.) In this manner, the voice of the user may be presented to the user of the other audio system in real time–which can be particularly helpful in a noisy environment (e.g., in a crowd at a football game or some other low acoustic SNR environment) where that other user would have difficulty hearing the user’s voice.

[0062] FIG. 3 is a flowchart illustrating a process 300 for near and far field signal enhancement via an audio system that uses a contact transducer, in accordance with one or more embodiments. The process shown in FIG. 3 may be performed by components of an audio system (e.g., audio system 200). Other entities may perform some or all of the steps in FIG. 3 in other embodiments. Embodiments may include different and/or additional steps, or perform the steps in different orders.

[0063] The audio system detects 310 sounds from a local area, the sounds including a voice of a user of the audio system. The audio system detects the sound using a transducer array (e.g., the transducer array 210). The detected sound includes the voice of the user and may also include sounds from other sound sources in the local area.

[0064] The audio system detects 320 tissue based vibrations that are generated by the user. The tissue based vibrations are generated by the voice of the user and are detected as the tissue based vibrations by one or more contact transducers in contact with portions of a head of the user. While the transducer array is capturing sound from the local area, one or more contact transducers monitor the user for tissue based vibrations. As such, the user’s voice is detected by the audio system in the tissue based vibrations as well as the sound detected by the sensor array.

[0065] The audio system identifies 330 the voice of the user in the detected sounds based in part on the detected tissue based vibrations and a signal processing and/or machine learning model. The signal processing and/or machine learning model uses the detected tissue based vibrations to identify the voice of the user within the detected sounds.

[0066] The audio system may use the detected tissue vibrations and the detected sounds in a number of ways. The output signals from the one or more contact transducers may be used as a VAD for training an adaptive beamformer (wearer-voice signal enhancement algorithm). The trained adaptive beamformer may be able to better distinguish between different sounds from different sound sources in a local area. In another example, the controller may determine spectral and spatial correlations of the voice of the user and the sounds from the local area using the tissue based vibrations. The controller may train the signal processing and/or machine learning model using the determined spectral and spatial correlations to distinguish the voice of the user from other sounds in the local area. In another example, the controller may determine one or more functions (e.g., temporal response, spectral response, spatial response) describing the user’s voice within the local area using the tissue based vibrations. The controller can train the signal processing and/or machine learning model using the determined one or more functions to distinguish between the user’s voice and other interfering sounds within the local area.

[0067] The audio system updates 340 a sound filter based on the identified voice of the user. The audio system 340 may, e.g., update a sound filter to enhance the voice of the user. The sound filter may enhance the voice of the user or suppress it while enhancing other voices. When enhancing the user’s voice the audio system may attempt to maintain a distortionless user’s voice with good quality and intelligibility whilst reducing noises or unwanted sounds for applications of voip/telephone communication. For applications of automatic speech recognition (ASR) the sound filters can attempt to minimize metrics such as word error rate (WER) or measures that determine the error in speech recognition (in these applications intelligibility and quality are not critical). In applications where the user’s voice is suppressed, for example to prevent feedback of the users own voice when enhancing a conversation for that user, the effects of the filters may be to minimize metrics of user voice energy, for example. In some embodiments, the audio system modifies the audio content using the updated sound filter. The audio system may then, e.g., present the modified audio content to the user (e.g., via a transducer array). In some embodiments, the audio system modifies the audio content with the updated filter, and the modified audio content enhances the voice of the user. The audio system may, e.g., determine that the modified audio content includes a command, and perform an action in accordance with the command. In some embodiments the audio system provides (e.g., via a local wireless network) the modified audio content to some other audio system in the local area, and the other audio system presents the modified audio content to its user. In this manner, the voice of the user may be presented to the user of the other audio system–which can be particularly helpful in noisy environments (i.e., a low acoustic SNR environment).

[0068] FIG. 4 is a system 400 that includes a headset 405, in accordance with one or more embodiments. In some embodiments, the headset 405 may be the headset 100 of FIG. 1A or the headset 105 of FIG. 1B. The system 400 may operate in an artificial reality environment (e.g., a virtual reality environment, an augmented reality environment, a mixed reality environment, or some combination thereof). The system 400 shown by FIG. 4 includes the headset 405, an input/output (I/O) interface 410 that is coupled to a console 415, the network 420, and the mapping server 425. While FIG. 4 shows an example system 400 including one headset 405 and one I/O interface 410, in other embodiments any number of these components may be included in the system 400. For example, there may be multiple headsets each having an associated I/O interface 410, with each headset and I/O interface 410 communicating with the console 415. In alternative configurations, different and/or additional components may be included in the system 400. Additionally, functionality described in conjunction with one or more of the components shown in FIG. 4 may be distributed among the components in a different manner than described in conjunction with FIG. 4 in some embodiments. For example, some or all of the functionality of the console 415 may be provided by the headset 405.

[0069] The headset 405 includes the display assembly 430, an optics block 435, one or more position sensors 440, and the DCA 445. Some embodiments of headset 405 have different components than those described in conjunction with FIG. 4. Additionally, the functionality provided by various components described in conjunction with FIG. 4 may be differently distributed among the components of the headset 405 in other embodiments, or be detected in separate assemblies remote from the headset 405.

[0070] The display assembly 430 displays content to the user in accordance with data received from the console 415. The display assembly 430 displays the content using one or more display elements (e.g., the display elements 120). A display element may be, e.g., an electronic display. In various embodiments, the display assembly 430 comprises a single display element or multiple display elements (e.g., a display for each eye of a user). Examples of an electronic display include: a liquid crystal display (LCD), an organic light emitting diode (OLED) display, an active-matrix organic light-emitting diode display (AMOLED), a waveguide display, some other display, or some combination thereof. Note in some embodiments, the display element 120 may also include some or all of the functionality of the optics block 435.

[0071] The optics block 435 may magnify image light received from the electronic display, corrects optical errors associated with the image light, and presents the corrected image light to one or both eyeboxes of the headset 405. In various embodiments, the optics block 435 includes one or more optical elements. Example optical elements included in the optics block 435 include: an aperture, a Fresnel lens, a convex lens, a concave lens, a filter, a reflecting surface, or any other suitable optical element that affects image light. Moreover, the optics block 435 may include combinations of different optical elements. In some embodiments, one or more of the optical elements in the optics block 435 may have one or more coatings, such as partially reflective or anti-reflective coatings.

[0072] Magnification and focusing of the image light by the optics block 435 allows the electronic display to be physically smaller, weigh less, and consume less power than larger displays. Additionally, magnification may increase the field of view of the content presented by the electronic display. For example, the field of view of the displayed content is such that the displayed content is presented using almost all (e.g., approximately 110 degrees diagonal), and in some cases, all of the user’s field of view. Additionally, in some embodiments, the amount of magnification may be adjusted by adding or removing optical elements.

[0073] In some embodiments, the optics block 435 may be designed to correct one or more types of optical error. Examples of optical error include barrel or pincushion distortion, longitudinal chromatic aberrations, or transverse chromatic aberrations. Other types of optical errors may further include spherical aberrations, chromatic aberrations, or errors due to the lens field curvature, astigmatisms, or any other type of optical error. In some embodiments, content provided to the electronic display for display is pre-distorted, and the optics block 435 corrects the distortion when it receives image light from the electronic display generated based on the content.

[0074] The position sensor 440 is an electronic device that generates data indicating a position of the headset 405. The position sensor 440 generates one or more measurement signals in response to motion of the headset 405. The position sensor 190 is an embodiment of the position sensor 440. Examples of a position sensor 440 include: one or more IMUs, one or more accelerometers, one or more gyroscopes, one or more magnetometers, another suitable type of sensor that detects motion, or some combination thereof. The position sensor 440 may include multiple accelerometers to measure translational motion (forward/back, up/down, left/right) and multiple gyroscopes to measure rotational motion (e.g., pitch, yaw, roll). In some embodiments, an IMU rapidly samples the measurement signals and calculates the estimated position of the headset 405 from the sampled data. For example, the IMU integrates the measurement signals received from the accelerometers over time to estimate a velocity vector and integrates the velocity vector over time to determine an estimated position of a reference point on the headset 405. The reference point is a point that may be used to describe the position of the headset 405. While the reference point may generally be defined as a point in space, however, in practice the reference point is defined as a point within the headset 405.

[0075] The DCA 445 generates depth information for a portion of the local area. The DCA includes one or more imaging devices and a DCA controller. The DCA 445 may also include an illuminator. Operation and structure of the DCA 445 is described above with regard to FIG. 1A.

[0076] The audio system 450 provides audio content to a user of the headset 405. The audio system 450 is substantially the same as the audio system 200 describe above. The audio system 450 may comprise one or acoustic sensors, one or more transducers, one or more contact transducers, and an audio controller. As described above with regard to, e.g., FIGS. 1-3, output signals from the one or more contract transducers and a signal processing and/or machine learning model facilitate the audio system 450 performing well in low acoustic SNR environments. The audio system 450 may provide spatialized audio content to the user. In some embodiments, the audio system 450 may request acoustic parameters from the mapping server 425 over the network 420. The acoustic parameters describe one or more acoustic properties (e.g., room impulse response, a reverberation time, a reverberation level, etc.) of the local area. The audio system 450 may provide information describing at least a portion of the local area from e.g., the DCA 445 and/or location information for the headset 405 from the position sensor 440. The audio system 450 may generate one or more sound filters using one or more of the acoustic parameters received from the mapping server 425, and use the sound filters to provide audio content to the user.

[0077] The I/O interface 410 is a device that allows a user to send action requests and receive responses from the console 415. An action request is a request to perform a particular action. For example, an action request may be an instruction to start or end detect of image or video data, or an instruction to perform a particular action within an application. The I/O interface 410 may include one or more input devices. Example input devices include: a keyboard, a mouse, a game controller, or any other suitable device for receiving action requests and communicating the action requests to the console 415. An action request received by the I/O interface 410 is communicated to the console 415, which performs an action corresponding to the action request. In some embodiments, the I/O interface 410 includes an IMU that detects calibration data indicating an estimated position of the I/O interface 410 relative to an initial position of the I/O interface 410. In some embodiments, the I/O interface 410 may provide haptic feedback to the user in accordance with instructions received from the console 415. For example, haptic feedback is provided when an action request is received, or the console 415 communicates instructions to the I/O interface 410 causing the I/O interface 410 to generate haptic feedback when the console 415 performs an action.

[0078] The console 415 provides content to the headset 405 for processing in accordance with information received from one or more of: the DCA 445, the headset 405, and the I/O interface 410. In the example shown in FIG. 4, the console 415 includes an application store 455, a tracking module 460, and an engine 465. Some embodiments of the console 415 have different modules or components than those described in conjunction with FIG. 4. Similarly, the functions further described below may be distributed among components of the console 415 in a different manner than described in conjunction with FIG. 4. In some embodiments, the functionality discussed herein with respect to the console 415 may be implemented in the headset 405, or a remote system.

[0079] The application store 455 stores one or more applications for execution by the console 415. An application is a group of instructions, that when executed by a processor, generates content for presentation to the user. Content generated by an application may be in response to inputs received from the user via movement of the headset 405 or the I/O interface 410. Examples of applications include: gaming applications, conferencing applications, video playback applications, or other suitable applications.

[0080] The tracking module 460 tracks movements of the headset 405 or of the I/O interface 410 using information from the DCA 445, the one or more position sensors 440, or some combination thereof. For example, the tracking module 460 determines a position of a reference point of the headset 405 in a mapping of a local area based on information from the headset 405. The tracking module 460 may also determine positions of an object or virtual object. Additionally, in some embodiments, the tracking module 460 may use portions of data indicating a position of the headset 405 from the position sensor 440 as well as representations of the local area from the DCA 445 to predict a future location of the headset 405. The tracking module 460 provides the estimated or predicted future position of the headset 405 or the I/O interface 410 to the engine 465.

[0081] The engine 465 executes applications and receives position information, acceleration information, velocity information, predicted future positions, or some combination thereof, of the headset 405 from the tracking module 460. Based on the received information, the engine 465 determines content to provide to the headset 405 for presentation to the user. For example, if the received information indicates that the user has looked to the left, the engine 465 generates content for the headset 405 that mirrors the user’s movement in a virtual local area or in a local area augmenting the local area with additional content. Additionally, the engine 465 performs an action within an application executing on the console 415 in response to an action request received from the I/O interface 410 and provides feedback to the user that the action was performed. The provided feedback may be visual or audible feedback via the headset 405 or haptic feedback via the I/O interface 410.

[0082] The network 420 couples the headset 405 and/or the console 415 to the mapping server 425. The network 420 may include any combination of local area and/or wide area networks using both wireless and/or wired communication systems. For example, the network 420 may include the Internet, as well as mobile telephone networks. In one embodiment, the network 420 uses standard communications technologies and/or protocols. Hence, the network 420 may include links using technologies such as Ethernet, 802.11, worldwide interoperability for microwave access (WiMAX), 2G/3G/4G mobile communications protocols, digital subscriber line (DSL), asynchronous transfer mode (ATM), InfiniBand, PCI Express Advanced Switching, etc. Similarly, the networking protocols used on the network 420 can include multiprotocol label switching (MPLS), the transmission control protocol/Internet protocol (TCP/IP), the User Datagram Protocol (UDP), the hypertext transport protocol (HTTP), the simple mail transfer protocol (SMTP), the file transfer protocol (FTP), etc. The data exchanged over the network 420 can be represented using technologies and/or formats including image data in binary form (e.g. Portable Network Graphics (PNG)), hypertext markup language (HTML), extensible markup language (XML), etc. In addition, all or some of links can be encrypted using conventional encryption technologies such as secure sockets layer (SSL), transport layer security (TLS), virtual private networks (VPNs), Internet Protocol security (IPsec), etc.

[0083] The mapping server 425 may include a database that stores a virtual model describing a plurality of spaces, wherein one location in the virtual model corresponds to a current configuration of a local area of the headset 405. The mapping server 425 receives, from the headset 405 via the network 420, information describing at least a portion of the local area and/or location information for the local area. The user may adjust privacy settings to allow or prevent the headset 405 from transmitting information to the mapping server 425. The mapping server 425 determines, based on the received information and/or location information, a location in the virtual model that is associated with the local area of the headset 405. The mapping server 425 determines (e.g., retrieves) one or more acoustic parameters associated with the local area, based in part on the determined location in the virtual model and any acoustic parameters associated with the determined location. The mapping server 425 may transmit the location of the local area and any values of acoustic parameters associated with the local area to the headset 405.

[0084] One or more components of system 400 may contain a privacy module that stores one or more privacy settings for user data elements. The user data elements describe the user or the headset 405. For example, the user data elements may describe a physical characteristic of the user, an action performed by the user, a location of the user of the headset 405, a location of the headset 405, an HRTF for the user, etc. Privacy settings (or “access settings”) for a user data element may be stored in any suitable manner, such as, for example, in association with the user data element, in an index on an authorization server, in another suitable manner, or any suitable combination thereof.

[0085] A privacy setting for a user data element specifies how the user data element (or particular information associated with the user data element) can be accessed, stored, or otherwise used (e.g., viewed, shared, modified, copied, executed, surfaced, or identified). In some embodiments, the privacy settings for a user data element may specify a “blocked list” of entities that may not access certain information associated with the user data element. The privacy settings associated with the user data element may specify any suitable granularity of permitted access or denial of access. For example, some entities may have permission to see that a specific user data element exists, some entities may have permission to view the content of the specific user data element, and some entities may have permission to modify the specific user data element. The privacy settings may allow the user to allow other entities to access or store user data elements for a finite period of time.

[0086] The privacy settings may allow a user to specify one or more geographic locations from which user data elements can be accessed. Access or denial of access to the user data elements may depend on the geographic location of an entity who is attempting to access the user data elements. For example, the user may allow access to a user data element and specify that the user data element is accessible to an entity only while the user is in a particular location. If the user leaves the particular location, the user data element may no longer be accessible to the entity. As another example, the user may specify that a user data element is accessible only to entities within a threshold distance from the user, such as another user of a headset within the same local area as the user. If the user subsequently changes location, the entity with access to the user data element may lose access, while a new group of entities may gain access as they come within the threshold distance of the user.

[0087] The system 400 may include one or more authorization/privacy servers for enforcing privacy settings. A request from an entity for a particular user data element may identify the entity associated with the request and the user data element may be sent only to the entity if the authorization server determines that the entity is authorized to access the user data element based on the privacy settings associated with the user data element. If the requesting entity is not authorized to access the user data element, the authorization server may prevent the requested user data element from being retrieved or may prevent the requested user data element from being sent to the entity. Although this disclosure describes enforcing privacy settings in a particular manner, this disclosure contemplates enforcing privacy settings in any suitable manner.

Additional Configuration Information

[0088] The foregoing description of the embodiments has been presented for illustration; it is not intended to be exhaustive or to limit the patent rights to the precise forms disclosed. Persons skilled in the relevant art can appreciate that many modifications and variations are possible considering the above disclosure.

[0089] Some portions of this description describe the embodiments in terms of algorithms and symbolic representations of operations on information. These algorithmic descriptions and representations are commonly used by those skilled in the data processing arts to convey the substance of their work effectively to others skilled in the art. These operations, while described functionally, computationally, or logically, are understood to be implemented by computer programs or equivalent electrical circuits, microcode, or the like. Furthermore, it has also proven convenient at times, to refer to these arrangements of operations as modules, without loss of generality. The described operations and their associated modules may be embodied in software, firmware, hardware, or any combinations thereof.

[0090] Any of the steps, operations, or processes described herein may be performed or implemented with one or more hardware or software modules, alone or in combination with other devices. In one embodiment, a software module is implemented with a computer program product comprising a computer-readable medium containing computer program code, which can be executed by a computer processor for performing any or all the steps, operations, or processes described.

[0091] Embodiments may also relate to an apparatus for performing the operations herein. This apparatus may be specially constructed for the required purposes, and/or it may comprise a general-purpose computing device selectively activated or reconfigured by a computer program stored in the computer. Such a computer program may be stored in a non-transitory, tangible computer readable storage medium, or any type of media suitable for storing electronic instructions, which may be coupled to a computer system bus. Furthermore, any computing systems referred to in the specification may include a single processor or may be architectures employing multiple processor designs for increased computing capability.

[0092] Embodiments may also relate to a product that is produced by a computing process described herein. Such a product may comprise information resulting from a computing process, where the information is stored on a non-transitory, tangible computer readable storage medium and may include any embodiment of a computer program product or other data combination described herein.

[0093] Finally, the language used in the specification has been principally selected for readability and instructional purposes, and it may not have been selected to delineate or circumscribe the patent rights. It is therefore intended that the scope of the patent rights be limited not by this detailed description, but rather by any claims that issue on an application based hereon. Accordingly, the disclosure of the embodiments is intended to be illustrative, but not limiting, of the scope of the patent rights, which is set forth in the following claims.

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