Abstract: A device includes a memory configured to store category labels associated with categories of a natural language processing library. A processor is configured to analyze input audio data to generate a text string and to perform natural language processing on at least the text string to generate an output text string including an action associated with a first device, a speaker, a location, or a combination thereof. The processor is configured to compare the input audio data to audio data of the categories to determine whether the input audio data matches any of the categories and, in response to determining that the input audio data does not match any of the categories: create a new category label, associate the new category label with at least a portion of the output text string, update the categories with the new category label, and generate a notification indicating the new category label.

Abstract: Methods, systems, and devices for signal processing are described. Generally, as provided for by the described techniques, a wearable device may receive an input audio signal (e.g., including both an external signal and a self-voice signal). The wearable device may detect the self-voice signal in the input audio signal based on a self-voice activity detection (SVAD) procedure, and may implement the described techniques based thereon. The wearable device may perform beamforming operations or other separation procedures to isolate the external signal and the self-voice signal from the input audio signal. The wearable device may apply a first filter to the external signal, and a second filter to the self-voice signal. The wearable device may then mix the filtered signals, and generate an output signal that sounds natural to the user.

Abstract: A device includes a processor configured to receive audio data samples and provide the audio data samples to a first neural network to generate a first output corresponding to a first set of sound classes. The processor is further configured to provide the audio data samples to a second neural network to generate a second output corresponding to a second set of sound classes. A second count of classes of the second set of sound classes is greater than a first count of classes of the first set of sound classes. The processor is also configured to provide the first output to a neural adapter to generate a third output corresponding to the second set of sound classes. The processor is further configured to provide the second output and the third output to a merger adapter to generate sound event identification data based on the audio data samples.

Abstract: A device includes a processor configured to determine a feature vector based on an utterance and to determine a first embedding vector by processing the feature vector using a trained embedding network. The processor is configured to determine a first distance metric based on distances between the first embedding vector and each embedding vector of a speaker template. The processor is configured to determine, based on the first distance metric, that the utterance is verified to be from a particular user. The processor is configured to, based on a comparison of a first particular distance metric associated with the first embedding vector to a second distance metric associated with a first test embedding vector of the speaker template, generate an updated speaker template by adding the first embedding vector as a second test embedding vector and removing the first test embedding vector from test embedding vectors of the speaker template.

Abstract: A device includes one or more processors configured to perform signal processing including a linear transformation and a non-linear transformation of an input signal to generate a reference target signal. The reference target signal has a linear component associated with the linear transformation and a non-linear component associated with the non-linear transformation. The one or more processors are also configured to perform linear filtering of the input signal by controlling adaptation of the linear filtering to generate an output signal that substantially matches the linear component of the reference target signal.

Abstract: Methods, systems, and devices for auditory enhancement are described. A device may receive a respective auditory signal at each of a set of microphones, where each auditory signal includes a respective representation of a target auditory component and one or more noise artifacts. The device may identify a directionality associated with a source of the target auditory component (e.g., based on an arrangement of the multiple microphones). The device may determine a distribution function for the target auditory component based at least in part on the directionality associated with the source and on the received plurality of auditory signals. The device may generate an estimate of the target auditory component based at least in part on the distribution function and output the estimate of the target auditory component.

Abstract: Methods, systems, computer-readable media, and apparatuses for signal enhancement are presented. One example of such an apparatus includes a receiver configured to produce a remote speech signal from information carried by a wireless signal; a signal canceller configured to perform a signal cancellation operation on a local speech signal to generate a room response; and a filter configured to filter the remote speech signal according to the room response to produce a filtered speech signal. In this example, the signal cancellation operation is based on the remote speech signal as a reference signal.

Abstract: Methods, systems, and devices for signal processing are described. Generally, in one example as provided for by the described techniques, a wearable device includes a processor configured to retrieve a plurality of external microphone signals that includes audio sound from outside of the device from a memory; to separate, based on at least information from an internal microphone signal, a self-voice component from a background component; to perform a first listen-through operation on the separated self-voice component to produce a first listen-through signal; and to produce an output audio signal that is based on at least the first listen-through signal, wherein the output audio signal includes an audio zoom signal that includes audio sound of the plurality of external microphone signals.

Abstract: An electronic device includes a display, wherein the display is configured to present a user interface, wherein the user interface comprises a coordinate system. The coordinate system corresponds to physical coordinates. The display is configured to present a sector selection feature that allows selection of at least one sector of the coordinate system. The at least one sector corresponds to captured audio from multiple microphones. The sector selection may also include an audio signal indicator. The electronic device includes operation circuitry coupled to the display. The operation circuitry is configured to perform an audio operation on the captured audio corresponding to the audio signal indicator based on the sector selection.

Abstract: A device for multi-modal user input includes a processor configured to process first data received from a first input device. The first data indicates a first input from a user based on a first input mode. The first input corresponds to a command. The processor is configured to send a feedback message to an output device based on processing the first data. The feedback message instructs the user to provide, based on a second input mode that is different from the first input mode, a second input that identifies a command associated with the first input. The processor is configured to receive second data from a second input device, the second data indicating the second input, and to update a mapping to associate the first input to the command identified by the second input.

Abstract: A device for activity tracking includes a memory and one or more processors. The memory is configured to store an activity log. The one or more processors are configured to update the activity log based on activity data. The activity data is received from a second device. The one or more processors are also configured to, responsive to receiving a natural language query, generate a query response based on the activity log.

Abstract: An apparatus includes a speech processing engine configured to receive data corresponding to speech and to determine whether a first characteristic associated with the speech differs from a reference characteristic by at least a threshold amount. The apparatus further includes a selection circuit responsive to the speech processing engine. The selection circuit is configured to select a particular speech codebook from among a plurality of speech codebooks based on the first characteristic differing from the reference characteristic by at least the threshold amount. The particular speech codebook is associated with the first characteristic.

Abstract: A device includes a memory configured to store a user experience evaluation unit. A processor is configured to receive a first user input corresponding to a user command to initiate a particular task, the first user input received via a first sensor. The processor is configured to, after receiving the first user input, receive one or more subsequent user inputs, the one or subsequent user inputs including a second user input received via a second sensor. The processor is configured to initiate a remedial action in response to determining, based on the user experience evaluation unit, that the one or more subsequent user inputs correspond to a negative user experience.

Abstract: A device includes a memory and one or more processors coupled to the memory. The one or more processors are configured to perform an active noise cancellation (ANC) operation on noisy input speech as captured by a first microphone, the noisy input speech as captured by a second microphone, or both, to suppress a noise level associated with the noisy input speech. The one or more processors are configured to match a second frequency spectrum of a second signal with a first frequency spectrum of a first signal. The first signal is representative of the noisy input speech as captured by the first microphone, and the second signal is representative of the noisy input speech as captured by the second microphone. The one or more processors are also configured to generate an output speech signal that is representative of input speech based on the second signal.

Abstract: Methods, systems, and devices for head-related transfer function generation are described. A device may receive a digital representation of a first audio signal associated with a location relative to a subject, and select from a database a first reference head-related transfer function measurement pair corresponding to the location of the first audio signal. The device may then obtain a second head-related transfer function measurement pair by performing a style transfer operation on the selected reference head-related transfer function measurement pair based on a set of head-related transfer function measurement pairs specific to the subject. As a result, the device may output a second audio signal based on the digital representation of the first audio signal and the second head-related transfer function measurement pair.

Abstract: A device includes a memory and one or more processors coupled to the memory. The one or more processors are configured to perform an active noise cancellation (ANC) operation on noisy input speech as captured by a first microphone, the noisy input speech as captured by a second microphone, or both, to suppress a noise level associated with the noisy input speech. The one or more processors are configured to match a second frequency spectrum of a second signal with a first frequency spectrum of a first signal. The first signal is representative of the noisy input speech as captured by the first microphone, and the second signal is representative of the noisy input speech as captured by the second microphone. The one or more processors are also configured to generate an output speech signal that is representative of input speech based on the second signal.

Abstract: A device to provide information to a visual interface that is mountable to a vehicle dashboard includes a memory configured to store device information indicative of controllable devices of a building and occupant data indicative of one or more occupants of the building. The device includes a processor configured to receive, in real-time, status information associated with the one or more occupants of the building. The status information includes at least one of dynamic location information or dynamic activity information. The processor is configured to generate an output to provide, at the visual interface device, a visual representation of at least a portion of the building and the status information associated with the one or more occupants. The processor is also configured to generate an instruction to adjust an operation of one or more devices of the controllable devices based on user input.

Abstract: Methods, systems, computer-readable media, and apparatuses for HRTF profile selection are presented. In one example, a device prompts a user to follow a simple procedure to obtain measurements that are matched to a suitable high-resolution HRTF profile.

Abstract: Methods, systems, and devices for signal processing are described. Generally, in one example as provided for by the described techniques, a wearable device includes a processor configured to retrieve a plurality of external microphone signals that includes audio sound from outside of the device from a memory; to separate, based on at least information from an internal microphone signal, a self-voice component from a background component; to perform a first listen-through operation on the separated self-voice component to produce a first listen-through signal; and to produce an output audio signal that is based on at least the first listen-through signal, wherein the output audio signal includes an audio zoom signal that includes audio sound of the plurality of external microphone signals.

Abstract: In a particular aspect, a speech generator includes a signal input configured to receive a first audio signal. The speech generator also includes at least one speech signal processor configured to generate a second audio signal based on information associated with the first audio signal and based further on automatic speech recognition (ASR) data associated with the first audio signal.