Patent ID: 12212948

DETAILED DESCRIPTION

In the following description of examples, reference is made to the accompanying drawings which form a part hereof, and in which it is shown by way of illustration specific examples that can be practiced. It is to be understood that other examples can be used and structural changes can be made without departing from the scope of the disclosed examples.

Example Wearable System

FIG.1illustrates an example wearable head device100configured to be worn on the head of a user. Wearable head device100may be part of a broader wearable system that comprises one or more components, such as a head device (e.g., wearable head device100), a handheld controller (e.g., handheld controller200described below), and/or an auxiliary unit (e.g., auxiliary unit300described below). In some examples, wearable head device100can be used for virtual reality, augmented reality, or mixed reality systems or applications. Wearable head device100can comprise one or more displays, such as displays110A and110B (which may comprise left and right transmissive displays, and associated components for coupling light from the displays to the user's eyes, such as orthogonal pupil expansion (OPE) grating sets112A/112B and exit pupil expansion (EPE) grating sets114A/114B); left and right acoustic structures, such as speakers120A and120B (which may be mounted on temple arms122A and122B, and positioned adjacent to the user's left and right ears, respectively); one or more sensors such as infrared sensors, accelerometers, GPS units, inertial measurement units (IMU) (e.g. IMU126), acoustic sensors (e.g., microphone150); orthogonal coil electromagnetic receivers (e.g., receiver127shown mounted to the left temple arm122A); left and right cameras (e.g., depth (time-of-flight) cameras130A and130B) oriented away from the user; and left and right eye cameras oriented toward the user (e.g., for detecting the user's eye movements)(e.g., eye cameras128and128B). However, wearable head device100can incorporate any suitable display technology, and any suitable number, type, or combination of sensors or other components without departing from the scope of the invention. In some examples, wearable head device100may incorporate one or more microphones150configured to detect audio signals generated by the user's voice; such microphones may be positioned in a wearable head device adjacent to the user's mouth. In some examples, wearable head device100may incorporate networking features (e.g., Wi-Fi capability) to communicate with other devices and systems, including other wearable systems. Wearable head device100may further include components such as a battery, a processor, a memory, a storage unit, or various input devices (e.g., buttons, touchpads); or may be coupled to a handheld controller (e.g., handheld controller200) or an auxiliary unit (e.g., auxiliary unit300) that comprises one or more such components. In some examples, sensors may be configured to output a set of coordinates of the head-mounted unit relative to the user's environment, and may provide input to a processor performing a Simultaneous Localization and Mapping (SLAM) procedure and/or a visual odometry algorithm. In some examples, wearable head device100may be coupled to a handheld controller200, and/or an auxiliary unit300, as described further below.

FIG.2illustrates an example mobile handheld controller component200of an example wearable system. In some examples, handheld controller200may be in wired or wireless communication with wearable head device100and/or auxiliary unit300described below. In some examples, handheld controller200includes a handle portion220to be held by a user, and one or more buttons240disposed along a top surface210. In some examples, handheld controller200may be configured for use as an optical tracking target; for example, a sensor (e.g., a camera or other optical sensor) of wearable head device100can be configured to detect a position and/or orientation of handheld controller200which may, by extension, indicate a position and/or orientation of the hand of a user holding handheld controller200. In some examples, handheld controller200may include a processor, a memory, a storage unit, a display, or one or more input devices, such as described above. In some examples, handheld controller200includes one or more sensors (e.g., any of the sensors or tracking components described above with respect to wearable head device100). In some examples, sensors can detect a position or orientation of handheld controller200relative to wearable head device100or to another component of a wearable system. In some examples, sensors may be positioned in handle portion220of handheld controller200, and/or may be mechanically coupled to the handheld controller. Handheld controller200can be configured to provide one or more output signals, corresponding, for example, to a pressed state of the buttons240; or a position, orientation, and/or motion of the handheld controller200(e.g., via an IMU). Such output signals may be used as input to a processor of wearable head device100, to auxiliary unit300, or to another component of a wearable system. In some examples, handheld controller200can include one or more microphones to detect sounds (e.g., a user's speech, environmental sounds), and in some cases provide a signal corresponding to the detected sound to a processor (e.g., a processor of wearable head device100).

FIG.3illustrates an example auxiliary unit300of an example wearable system. In some examples, auxiliary unit300may be in wired or wireless communication with wearable head device100and/or handheld controller200. The auxiliary unit300can include a battery to provide energy to operate one or more components of a wearable system, such as wearable head device100and/or handheld controller200(including displays, sensors, acoustic structures, processors, microphones, and/or other components of wearable head device100or handheld controller200). In some examples, auxiliary unit300may include a processor, a memory, a storage unit, a display, one or more input devices, and/or one or more sensors, such as described above. In some examples, auxiliary unit300includes a clip310for attaching the auxiliary unit to a user (e.g., a belt worn by the user). An advantage of using auxiliary unit300to house one or more components of a wearable system is that doing so may allow large or heavy components to be carried on a user's waist, chest, or back—which are relatively well-suited to support large and heavy objects—rather than mounted to the user's head (e.g., if housed in wearable head device100) or carried by the user's hand (e.g., if housed in handheld controller200). This may be particularly advantageous for relatively heavy or bulky components, such as batteries.

FIG.4shows an example functional block diagram that may correspond to an example wearable system400, such as may include example wearable head device100, handheld controller200, and auxiliary unit300described above. In some examples, the wearable system400could be used for virtual reality, augmented reality, or mixed reality applications. As shown inFIG.4, wearable system400can include example handheld controller400B, referred to here as a “totem” (and which may correspond to handheld controller200described above); the handheld controller400B can include a totem-to-headgear six degree of freedom (6DOF) totem subsystem404A. Wearable system400can also include example wearable head device400A (which may correspond to wearable headgear device100described above); the wearable head device400A includes a totem-to-headgear 6DOF headgear subsystem404B. In the example, the 6DOF totem subsystem404A and the 6DOF headgear subsystem404B cooperate to determine six coordinates (e.g., offsets in three translation directions and rotation along three axes) of the handheld controller400B relative to the wearable head device400A. The six degrees of freedom may be expressed relative to a coordinate system of the wearable head device400A. The three translation offsets may be expressed as X, Y, and Z offsets in such a coordinate system, as a translation matrix, or as some other representation. The rotation degrees of freedom may be expressed as sequence of yaw, pitch, and roll rotations; as vectors; as a rotation matrix; as a quaternion; or as some other representation. In some examples, one or more depth cameras444(and/or one or more non-depth cameras) included in the wearable head device400A; and/or one or more optical targets (e.g., buttons240of handheld controller200as described above, or dedicated optical targets included in the handheld controller) can be used for 6DOF tracking. In some examples, the handheld controller400B can include a camera, as described above; and the headgear400A can include an optical target for optical tracking in conjunction with the camera. In some examples, the wearable head device400A and the handheld controller400B each include a set of three orthogonally oriented solenoids which are used to wirelessly send and receive three distinguishable signals. By measuring the relative magnitude of the three distinguishable signals received in each of the coils used for receiving, the 6DOF of the handheld controller400B relative to the wearable head device400A may be determined. In some examples, 6DOF totem subsystem404A can include an Inertial Measurement Unit (IMU) that is useful to provide improved accuracy and/or more timely information on rapid movements of the handheld controller400B.

In some examples involving augmented reality or mixed reality applications, it may be desirable to transform coordinates from a local coordinate space (e.g., a coordinate space fixed relative to wearable head device400A) to an inertial coordinate space, or to an environmental coordinate space. For instance, such transformations may be necessary for a display of wearable head device400A to present a virtual object at an expected position and orientation relative to the real environment (e.g., a virtual person sitting in a real chair, facing forward, regardless of the position and orientation of wearable head device400A), rather than at a fixed position and orientation on the display (e.g., at the same position in the display of wearable head device400A). This can maintain an illusion that the virtual object exists in the real environment (and does not, for example, appear positioned unnaturally in the real environment as the wearable head device400A shifts and rotates). In some examples, a compensatory transformation between coordinate spaces can be determined by processing imagery from the depth cameras444(e.g., using a Simultaneous Localization and Mapping (SLAM) and/or visual odometry procedure) in order to determine the transformation of the wearable head device400A relative to an inertial or environmental coordinate system. In the example shown inFIG.4, the depth cameras444can be coupled to a SLAM/visual odometry block406and can provide imagery to block406. The SLAM/visual odometry block406implementation can include a processor configured to process this imagery and determine a position and orientation of the user's head, which can then be used to identify a transformation between a head coordinate space and a real coordinate space. Similarly, in some examples, an additional source of information on the user's head pose and location is obtained from an IMU409of wearable head device400A. Information from the IMU409can be integrated with information from the SLAM/visual odometry block406to provide improved accuracy and/or more timely information on rapid adjustments of the user's head pose and position.

In some examples, the depth cameras444can supply 3D imagery to a hand gesture tracker411, which may be implemented in a processor of wearable head device400A. The hand gesture tracker411can identify a user's hand gestures, for example, by matching 3D imagery received from the depth cameras444to stored patterns representing hand gestures. Other suitable techniques of identifying a user's hand gestures will be apparent.

In some examples, one or more processors416may be configured to receive data from headgear subsystem404B, the IMU409, the SLAM/visual odometry block406, depth cameras444, a microphone (not shown); and/or the hand gesture tracker411. The processor416can also send and receive control signals from the 6DOF totem system404A. The processor416may be coupled to the 6DOF totem system404A wirelessly, such as in examples where the handheld controller400B is untethered. Processor416may further communicate with additional components, such as an audio-visual content memory418, a Graphical Processing Unit (GPU)420, and/or a Digital Signal Processor (DSP) audio spatializer422. The DSP audio spatializer422may be coupled to a Head Related Transfer Function (HRTF) memory425. The GPU420can include a left channel output coupled to the left source of imagewise modulated light424and a right channel output coupled to the right source of imagewise modulated light426. GPU420can output stereoscopic image data to the sources of imagewise modulated light424,426. The DSP audio spatializer422can output audio to a left speaker412and/or a right speaker414. The DSP audio spatializer422can receive input from processor416indicating a direction vector from a user to a virtual sound source (which may be moved by the user, e.g., via the handheld controller400B). Based on the direction vector, the DSP audio spatializer422can determine a corresponding HRTF (e.g., by accessing a HRTF, or by interpolating multiple HRTFs). The DSP audio spatializer422can then apply the determined HRTF to an audio signal, such as an audio signal corresponding to a virtual sound generated by a virtual object. This can enhance the believability and realism of the virtual sound, by incorporating the relative position and orientation of the user relative to the virtual sound in the mixed reality environment that is, by presenting a virtual sound that matches a user's expectations of what that virtual sound would sound like if it were a real sound in a real environment.

In some examples, such as shown inFIG.4, one or more of processor416, GPU420, DSP audio spatializer422, HRTF memory425, and audio/visual content memory418may be included in an auxiliary unit400C (which may correspond to auxiliary unit300described above). The auxiliary unit400C may include a battery427to power its components and/or to supply power to wearable head device400A and/or handheld controller400B. Including such components in an auxiliary unit, which can be mounted to a user's waist, can limit the size and weight of wearable head device400A, which can in turn reduce fatigue of a user's head and neck.

WhileFIG.4presents elements corresponding to various components of an example wearable system400, various other suitable arrangements of these components will become apparent to those skilled in the art. For example, elements presented inFIG.4as being associated with auxiliary unit400C could instead be associated with wearable head device400A or handheld controller400B. Furthermore, some wearable systems may forgo entirely a handheld controller400B or auxiliary unit400C. Such changes and modifications are to be understood as being included within the scope of the disclosed examples.

Mixed Reality Environment

Like all people, a user of a mixed reality system exists in a real environment that is, a three-dimensional portion of the “real world,” and all of its contents, that are perceptible by the user. For example, a user perceives a real environment using one's ordinary human senses sight, sound, touch, taste, smell and interacts with the real environment by moving one's own body in the real environment. Locations in a real environment can be described as coordinates in a coordinate space; for example, a coordinate can comprise latitude, longitude, and elevation with respect to sea level; distances in three orthogonal dimensions from a reference point; or other suitable values. Likewise, a vector can describe a quantity having a direction and a magnitude in the coordinate space.

A computing device can maintain, for example, in a memory associated with the device, a representation of a virtual environment. As used herein, a virtual environment is a computational representation of a three-dimensional space. A virtual environment can include representations of any object, action, signal, parameter, coordinate, vector, or other characteristic associated with that space. In some examples, circuitry (e.g., a processor) of a computing device can maintain and update a state of a virtual environment; that is, a processor can determine at a first time, based on data associated with the virtual environment and/or input provided by a user, a state of the virtual environment at a second time. For instance, if an object in the virtual environment is located at a first coordinate at time, and has certain programmed physical parameters (e.g., mass, coefficient of friction); and an input received from user indicates that a force should be applied to the object in a direction vector; the processor can apply laws of kinematics to determine a location of the object at time using basic mechanics. The processor can use any suitable information known about the virtual environment, and/or any suitable input, to determine a state of the virtual environment at a time. In maintaining and updating a state of a virtual environment, the processor can execute any suitable software, including software relating to the creation and deletion of virtual objects in the virtual environment; software (e.g., scripts) for defining behavior of virtual objects or characters in the virtual environment; software for defining the behavior of signals (e.g., audio signals) in the virtual environment; software for creating and updating parameters associated with the virtual environment; software for generating audio signals in the virtual environment; software for handling input and output; software for implementing network operations; software for applying asset data (e.g., animation data to move a virtual object over time); or many other possibilities.

Output devices, such as a display or a speaker, can present any or all aspects of a virtual environment to a user. For example, a virtual environment may include virtual objects (which may include representations of inanimate objects; people; animals; lights; etc.) that may be presented to a user. A processor can determine a view of the virtual environment (for example, corresponding to a “camera” with an origin coordinate, a view axis, and a frustum); and render, to a display, a viewable scene of the virtual environment corresponding to that view. Any suitable rendering technology may be used for this purpose. In some examples, the viewable scene may include only some virtual objects in the virtual environment, and exclude certain other virtual objects. Similarly, a virtual environment may include audio aspects that may be presented to a user as one or more audio signals. For instance, a virtual object in the virtual environment may generate a sound originating from a location coordinate of the object (e.g., a virtual character may speak or cause a sound effect); or the virtual environment may be associated with musical cues or ambient sounds that may or may not be associated with a particular location. A processor can determine an audio signal corresponding to a “listener” coordinate for instance, an audio signal corresponding to a composite of sounds in the virtual environment, and mixed and processed to simulate an audio signal that would be heard by a listener at the listener coordinate and present the audio signal to a user via one or more speakers.

Because a virtual environment exists only as a computational structure, a user cannot directly perceive a virtual environment using one's ordinary senses. Instead, a user can perceive a virtual environment only indirectly, as presented to the user, for example by a display, speakers, haptic output devices, etc. Similarly, a user cannot directly touch, manipulate, or otherwise interact with a virtual environment; but can provide input data, via input devices or sensors, to a processor that can use the device or sensor data to update the virtual environment. For example, a camera sensor can provide optical data indicating that a user is trying to move an object in a virtual environment, and a processor can use that data to cause the object to respond accordingly in the virtual environment.

Filtering Audio Signals

Systems and methods for filtering audio signals for rendering in a binaural environment (e.g., left and right speakers presenting audio to left and right ears, respectively, in an XR environment) are disclosed. According to embodiments, two input audio signals (or channels) are presented to a filter network, which generates two output audio signals (e.g., left and right signals) for presentation to a user in the binaural environment. The two input signals may correspond to first and second audio sources, such as microphones in a coincident-pair microphone recording, or first and second audio assets originating from first and second locations, respectively, in an XR environment. In some embodiments, a mid-side (M-S) matrix (also known as a stereo shuffler) can be a useful tool for filtering and presenting audio signals as described above. A “mid” component may be considered to be equivalent to a sum of a two-channel input signal, and a “side” component may be considered to be equivalent to a difference of the two-channel input signal.

FIG.5illustrates an implementation of a signal processing system500using M-S matrices, according to some embodiments. The M-S matrices may be implemented by calculating a sum and a difference of a two channel input signal (e.g., a first input signal (input1) and a second input signal (input2)), applying filtering to one or both of the channels (e.g., processing on sum or processing on difference), and calculating a sum and a difference of the filtered (e.g., processed) signals.

In the example shown inFIG.5, input1and input2are summed at stage510, with the sum processed at stage520; and input1and the inverse of input2are summed at stage512to generate a difference between input1and input2, with the difference processed at stage522. At stage530, the output of stage520and the output of stage522are summed to generate output1, which may be presented to a first speaker (e.g., a left speaker directed at a user's left ear). At stage532, the output of stage520and the inverse of the output of stage522are summed to generate output2, which may be presented to a second speaker (e.g., a right speaker directed at a user's right ear). Stages510,512,530, and532can be referred to as sum and difference networks.

FIG.6illustrates an implementation of a signal processing system600using M-S matrices, according to some embodiments. The M-S matrices may be implemented by calculating a sum and a difference of a two channel input signal (e.g., a first input signal (input1) and a second input signal (input2)), applying a gain to one or both of the intermediate channels (e.g., gain of 0.5), and calculating a sum and a difference of the gain-adjusted signals. Constraining the sum and difference to a gain of 0.5 may result in a unity system in which original signals (e.g., the first input signal and the second input signal) may be retained.

In the example shown inFIG.6, input1and input2are summed at stage610, with a gain factor of 0.5 applied to the sum at stage620(which can correspond to the processing stage520inFIG.5); and input1and the inverse of input2are summed at stage612to generate a difference between input1and input2, with a gain factor of 0.5 applied to the difference at stage622(which can correspond to the processing stage522inFIG.5). At stage630, the output of stage620and the output of stage622are summed to generate output1, which may be presented to a first speaker (e.g., a left speaker directed at a user's left ear). At stage632, the output of stage620and the inverse of the output of stage622are summed to generate output2, which may be presented to a second speaker (e.g., a right speaker directed at a user's right ear).

FIG.7illustrates an implementation of a signal processing system700using M-S matrices, according to some embodiments. The M-S shuffle may be implemented by calculating a sum and a difference of a two-channel input signal (e.g., a first input signal (input1) and a second input signal (input2)), applying a gain to one or both of the intermediate channels (e.g., gain of 0.5), filtering (e.g., via a first filter (filter1) and a second filter (filter2)) the gain-adjusted signals, and calculating a sum and a difference of the filtered gain-adjusted signals. As illustrated inFIG.7, filtering signals (e.g., via the first filter and the second filter) between M-S matrices may be cascaded with a gain of 0.5 for normalization.

In the example shown inFIG.7, input1and input2are summed at stage710, with a gain factor of 0.5 applied to the sum at stage720A, and a first filter applied at stage720B to the result. Stages720A and720B can together be considered a processing stage720, which can correspond to the processing stage520inFIG.5. Input1and the inverse of input2are summed at stage712to generate a difference between input1and input2, with a gain factor of 0.5 applied to the difference at stage722A, and a first filter applied at stage722B to the result. Stages722A and722B can together be considered a processing stage722, which can correspond to the processing stage522inFIG.5. At stage730, the output of processing stage720and the output of processing stage722are summed to generate output1, which may be presented to a first speaker (e.g., a left speaker directed at a user's left ear). At stage732, the output of stage720and the inverse of the output of stage722are summed to generate output2, which may be presented to a second speaker (e.g., a right speaker directed at a user's right ear).

In some embodiments, for example of signal processing, a M-S shuffle approach may be used to apply symmetrical stereo filters to two input signals.FIG.8illustrates a system800where two filters are applied to each input signal and summed to generate two output signals, according to some embodiments. For example, two filters (e.g., a first filter820A (“filter11”) and a second filter820B (“filter12”)) are applied to a first input signal (e.g., input1) and two filters (e.g., a third filter822A (“filter21”) and a fourth filter822B (“filter22”)) are applied to a second input signal (e.g., input2). The first input signal filtered by the first filter820A may be referred to as a first filtered signal, the first input signal filtered by the second filter820B may be referred to as a second filtered signal, the second input signal filtered by the third filter822A may be referred to as a third filtered signal, and the second input signal filtered by the fourth filter822B may be referred to as a fourth filtered signal. A first output (e.g., output1) may be a summation (stage830) of the first filtered signal and the third filtered signal, and a second output (e.g., output2) may be a summation (stage832) of the second filtered signal and the fourth filtered signal.

FIG.9illustrates an example system900where two filters are applied to each input signal and summed to generate two output signals, according to some embodiments. As in the example shown inFIG.8, two filters (e.g., a first filter920A (“filter11”) and a second filter920B (“filter12”)) are applied to a first input signal (e.g., input1) and two filters (e.g., a third filter922A (“filter12”) and a fourth filter922B (“filter11”)) are applied to a second input signal (e.g., input2). In some embodiments, such as shown inFIG.9, the first filter920A and the fourth filter922B may be identical filters, and the second filter (filter12) and the third filter (filter12) may be identical filters. The first input signal filtered by the first filter920A may be referred to as a first filtered signal, the first input signal filtered by the second filter920B may be referred to as a second filtered signal, the second input signal filtered by the third filter922A may be referred to as a third filtered signal, and the second input signal filtered by the fourth filter922B may be referred to as a fourth filtered signal. A first output (e.g., output1) may be a summation (stage930) of the first filtered signal and the third filtered signal, and a second output (e.g., output2) may be a summation (stage932) of the second filtered signal and the fourth filtered signal.

As illustrated in the example shown inFIG.9, symmetrical stereo filters may be applied to the two input signals (e.g., input1and input2). Referring toFIG.7, a M-S shuffle implementation of a system may be implemented where the first filter720B ofFIG.7may be equivalent to a summation of the first filter920A ofFIG.9and the second filter920B ofFIG.9, and the second filter722B ofFIG.7may be equivalent to a difference of the first filter920A ofFIG.9and the second filter920B ofFIG.9.

In some embodiments, digital filters may include leading and trailing zeros or samples with very small values, which may make the filters long. Such filters may require more computing resources (e.g., processor cycles, memory) than shorter filters.FIG.10illustrates an example filter impulse response1000with leading and trailing zeros, according to some embodiments.FIG.11illustrates a filter impulse response1100with no leading and trailing zeros, according to some embodiments. Compared to the example filter shown inFIG.10, the example filter shown inFIG.11may be smaller and more computationally efficient.

FIG.12illustrates an example audio rendering system1200, which includes an amplitude panning module1210followed by a virtual speaker array (VSA)1220made up of N virtual speakers. Each virtual speaker may be realized using, e.g., any one of the systems illustrated inFIGS.7,8, and9, according to some embodiments. The panning module1210can accept an audio input signal (e.g., a two-channel audio input such as described above with respect toFIGS.5-9), and present a processed (e.g., attenuated, amplified, and/or filtered) version of the audio input signal to each of the N virtual speakers. The gain of the signals presented to each of the N virtual speakers can be adjusted to achieve a desired signal balance across the VSA, with the outputs of each virtual speaker summed (stage1230) and presented as output to a user.

In some embodiments, filters (e.g., filters920A,920B,922A,922B ofFIG.9) may not be well aligned across sound source positions. Filters that are not well aligned across sound source positions may affect timbre quality of a binaural renderer output signal and may result in sf-5621623 timbre artifacts for example, destructive and constructive interferences depending on frequency as an audio signal is panned through a VSA. These artifacts can comprise the realism of sounds in a virtual environment.

In some embodiments, aligning a sum filter and a difference filter may reduce timbre artifacts during amplitude panning. For example, samples may be added or removed at a beginning of filters to obtain better alignment between filter pairs. A relative delay between filters within filter pairs, or inter-filter delays (IFDs) may be preserved.

In some embodiments, filters may be trimmed, for example, to retain “useful” portions thereof. In some examples, useful portions may be portions that contain non-zero, non-noise magnitude and/or phase information. Trimmed filters may require less computation to process than untrimmed filters. For example, trimming filters may include removing leading zeros or low level samples (e.g., samples that fall within a noise level of the filter, for example, where the noise level of the filter may be determined by analyzing a portion of a filter that is only noise and using that information to determine a noise gate threshold) at a beginning of some or all filters in a system. In some embodiments, a same number of leading zeros or low level samples must be removed from filters in a sum-difference filter pair, for example, to preserve/maintain IFDs. In some embodiments, trimming filters may include removing trailing zeros or low level samples at an end of some or all filter in a system. As described herein, trimming filters may include removing leading zeros or low level samples and/or removing trailing zeros or low level samples. The leading zeros or low level samples and/or the trailing zeros or low level samples may be identified, for example, by setting a level threshold and removing leading samples of a signal before the signal crosses the level threshold, by identifying a peak in an impulse response and applying a predetermined window around the identified peak, by identifying a peak in an envelope of an impulse response and applying a predetermined window around the identified peak, by trimming a filter to different length and analyzing a resulting magnitude and/or phase response to determine when the trimming starts introducing undesirable artifacts, and/or by trimming a filter to a different length and evaluating an introduced distortion by listening to audio content processed through the filters.

In some embodiments, filter alignment may be achieved by generating a minimum phase version of filters. In these embodiments, pre-ringing and pre-echo in filters may be removed/eliminated, which may allow further truncation of leading zeros and short filters.

FIG.13illustrates an example process1300for aligning sum and difference filters using a minimum phase approach, according to some embodiments. According to the example shown, raw filters1302may be converted to a frequency domain, e.g., using fast Fourier transforms (FFTs) (stage1304). IFDs may be measured (stage1306), for example by looking at a difference in excess phase at low frequencies between pairs of filters that are converted to the frequency domain, and may be stored for use later. At stage1308, the filters in the frequency domain may be pre-processed. In some embodiments, pre-processing may include applying a gain, equalizing, and/or smoothing the data. A minimum-phase version of the filters may be generated from the pre-processed filters (stage1310), and converted to a time domain using an inverse FFT (iFFT) (stage1312). The measured IFDs may be applied to the filters in the time domain (stage1314), e.g., in matching pairs to recreate the IFDs observed in the filters in the frequency domain. The filters with the IFD applied may be post-processed (stage1316), which in some examples may include forcing symmetry on some of the filter pairs by setting the difference filter to zero (which may have the benefit of further reducing the computational complexity of the signal processing system). In some embodiments, truncation (e.g., time-domain windowing) may be applied to reduce length of filters. The sum and difference filters may then be computed (stage1318) and stored for use (1320), for example, in a signal processing system.

In some embodiments, IFDs may be applied to a delayed filter only. In some embodiments, in the context of binaural rendering, applying IFDs to the delayed filter only may effectively time-align the filters for an ipsilateral ear. Since an ipsilateral ear signal may arrive in an ear first, and may be louder than a contralateral ear signal, better time alignment of ipsilateral ear filters may lead to better perceived timbre when panning audio content through a VSA using amplitude panning methods. In some embodiments, without time alignment of ipsilateral ear signals, spectral artifacts may be perceived as an audio signal is panned through the VSA, for example, due to constructive and destructive interference between misaligned signals.

In some embodiments, IFDs may be modified before applying the IFDs to filters at stage1314. The IFDs may be modified, for example, to remove measurement errors. In some embodiments, modification of IFDs may be used to tune the IFDs to match anthropometric features of the user. In some examples, sensors can be used to tune the IFDs. For instance, sensors such as depth cameras, RGB cameras, LIDAR, sonar, orientation sensors, GPS, and so forth can be used to determine relevant acoustic parameters that can be used to modify the IFDs in accordance with those parameters. Such sensors are described above with respect to hardware for interacting with XR environments (e.g., wearable head device100, handheld controller200, and/or auxiliary unit300described above) and the use of such sensors for determining IFDs may be particularly beneficial in such applications.

In some embodiments, alignment of filters may be achieved by setting a level threshold (e.g., a threshold above a noise level of a filter) and removing samples at a beginning of a filter to a point where a signal crosses a threshold. In some embodiments, computational power of processing and memory for storing filters may be reduced by setting a second threshold (e.g., a threshold based on a level relative to a peak of an impulse response, or an immediately preceding amplitude, or a time delay subsequent to a peak impulse response) and trimming trailing zeros in the filters.

In some embodiments, alignment filters may be achieved using a cross-correlation measure to find a lag providing a highest correlation between filter responses.

In some embodiments, alignment of filters may be done empirically be measuring a transfer function of a full rendering system through a VSA and picking an alignment that provides a least amount of magnitude or phase distortion to one or both ear signals.

In some embodiments, alignment of filters may be done empirically by listening to content, for example, content that is likely to reveal artifacts, panned through a VSA and picking an alignment that provides a least amount of perceived timbral artifacts.

In some embodiments, filters such as described above with respect toFIGS.5-13can comprise a head-related transfer function (HRTF) filter, such as described above with respect toFIG.400for spatializing audio sources, e.g., in a virtual environment. For example, filters920A,920B,922A, and922B of example system900may comprise ipsilateral and/or contralateral HRTF filters for two sound sources in locations placed symmetrically on either side of a user (e.g., on either side of a median (mid-sagittal) plane corresponding to the user).

In such embodiments, sum and difference filters may be created by pulling/fetching/retrieving raw filters (e.g., unprocessed filters that may be derived from measurements or simulations), for example, from a discrete HRTF database and computing a sum and a difference. In some examples, such as in XR environments, the selection and creation of such filters can be informed by the outputs of sensors able to detect parameters of the user and/or the user's environment, in order to arrive at HRTF filters that may be preferred by the user in that particular environment. Such parameters can include morphological parameters of the user (e.g., the user's height, head width, and other physical dimensions), environmental parameters (e.g., the dimensions of a room in the user's environment), or other parameters relevant to selecting a HRTF filter.

As an example, a user can be equipped with a wearable head device, such as device100described above, to interact with a XR environment. As described above, the wearable head device can include one or more sensors to detect parameters of the user and/or the environment. Such sensors can include depth cameras, RGB cameras, LIDAR, sonar, orientation sensors, GPS, and similar sensors; these sensors can be used to determine parameters relevant to HRTF selection (e.g., environmental parameters and/or morphological parameters of the user), and HRTF filters can be selected accordingly. In some cases, such parameters (e.g., the user's height) can be input by the user and stored in a wearable system for later use.

With respect to the systems and methods described above, elements of the systems and methods can be implemented by one or more computer processors (e.g., CPUs or DSPs) as appropriate. The disclosure is not limited to any particular configuration of computer hardware, including computer processors, used to implement these elements. In some cases, multiple computer systems can be employed to implement the systems and methods described above. For example, a first computer processor (e.g., a processor of a wearable device coupled to a microphone) can be utilized to receive input microphone signals, and perform initial processing of those signals (e.g., signal conditioning and/or segmentation, such as described above). A second (and perhaps more computationally powerful) processor can then be utilized to perform more computationally intensive processing, such as determining probability values associated with speech segments of those signals. Another computer device, such as a cloud server, can host a speech recognition engine, to which input signals are ultimately provided. Other suitable configurations will be apparent and are within the scope of the disclosure.

Although the disclosed examples have been fully described with reference to the accompanying drawings, it is to be noted that various changes and modifications will become apparent to those skilled in the art. For example, elements of one or more implementations may be combined, deleted, modified, or supplemented to form further implementations. Such changes and modifications are to be understood as being included within the scope of the disclosed examples as defined by the appended claims.