Abstract: A system is provided that employs a statistical approach to semi-supervised speech enhancement with a low-order non-negative matrix factorization (“NMF”). The system enhances noisy speech based on multiple dictionaries with dictionary atoms derived from the same clean speech samples and generates an enhanced speech representation of the noisy speech by combining, for each dictionary, a clean speech representation of the noisy speech generated based on a NMF using the dictionary atoms of the dictionary. The system generates frequency-domain (“FD”) clean speech sample representations of the clean speech samples, for example, using a Fourier transform. To generate each dictionary, the system generates a dictionary-unique initialization of the dictionary atoms and the activations and performs a NMF of the FD clean speech samples.

Abstract: An ultrasonic gesture recognition system is provided that recognizes gestures based on analysis of return signals of an ultrasonic pulse that is reflected from a gesture. The system transmits an ultrasonic chirp and samples a microphone array at sample intervals to collect a return signal for each microphone. The system then applies a beamforming technique to frequency domain representations of the return signals to generate an acoustic image with a beamformed return signal for multiple directions. The system then generates a feature image from the acoustic images to identify, for example, distance or depth from the microphone array to the gesture for each direction. The system then submits the feature image to a deep learning system to classify the gesture.

Abstract: Systems and methods of providing an audio signal are disclosed herein. In one embodiment, a method of delivering an audio signal from a device toward a user's ear includes, for example, transmitting a filtered audio signal from a transducer positioned at a location on the device that is longitudinally spaced apart from an entrance of an auditory canal of the user's ear when the device is worn on the user's head.

Abstract: Systems and methods of providing an audio signal are disclosed herein. In one embodiment, a method of producing an audio signal includes applying, for example, a head related transfer function (HRTF) and a transducer position compensation filter to an input audio signal to generate an enhanced audio signal configured to be transmitted toward an entrance of the user's ear from a transducer carried by a headset and spaced apart from the entrance to a user's ear.

Abstract: Systems and methods of providing an audio signal are disclosed herein. In one embodiment, a method of producing an audio signal includes applying, for example, a head related transfer function (HRTF) and a transducer position compensation filter to an input audio signal to generate an enhanced audio signal configured to be transmitted toward an entrance of the user's ear from a transducer carried by a headset and spaced apart from the entrance to a user's ear.

Abstract: A multichannel acoustic echo reduction system is described herein. The system includes an acoustic echo canceller (AEC) component having a fixed filter for each respective combination of loudspeaker and microphone signals and having an adaptive filter for each microphone signal. For each microphone signal, the AEC component modifies the microphone signal to reduce contributions from the outputs of the loudspeakers based at least in part on the respective adaptive filter associated with the microphone signal and the set of fixed filters associated with the respective microphone signal.

Abstract: Described is a audio signal processing technology in which an adaptive beamformer processes input signals from microphones based on an estimate received from a pre-filter. The adaptive beamformer may compute its parameters (e.g., weights) for each frame based on the estimate, via a magnitude-domain objective function or log-magnitude-domain objective function. The pre-filter may include a time invariant beamformer and/or a non-linear spatial filter, and/or may include a spectral filter. The computed parameters may be adjusted based on a constraint, which may be selectively applied only at desired times.

Abstract: A multichannel acoustic echo reduction system is described herein. The system includes an acoustic echo canceller (AEC) component having a fixed filter for each respective combination of loudspeaker and microphone signals and having an adaptive filter for each microphone signal. For each microphone signal, the AEC component modifies the microphone signal to reduce contributions from the outputs of the loudspeakers based at least in part on the respective adaptive filter associated with the microphone signal and the set of fixed filters associated with the respective microphone signal.

Abstract: Described is a audio signal processing technology in which an adaptive beamformer processes input signals from microphones based on an estimate received from a pre-filter. The adaptive beamformer may compute its parameters (e.g., weights) for each frame based on the estimate, via a magnitude-domain objective function or log-magnitude-domain objective function. The pre-filter may include a time invariant beamformer and/or a non-linear spatial filter, and/or may include a spectral filter. The computed parameters may be adjusted based on a constraint, which may be selectively applied only at desired times.

Abstract: A multichannel acoustic echo reduction system is described herein. The system includes an acoustic echo canceller (AEC) component having a fixed filter for each respective combination of loudspeaker and microphone signals and having an adaptive filter for each microphone signal. For each microphone signal, the AEC component modifies the microphone signal to reduce contributions from the outputs of the loudspeakers based at least in part on the respective adaptive filter associated with the microphone signal and the set of fixed filters associated with the respective microphone signal.