Abstract:
Systems, methods, and apparatus for pitch trajectory analysis are described. Such techniques may be used to remove vocals and/or vibrato from an audio mixture signal. For example, such a technique may be used to pre-process the signal before an operation to decompose the mixture signal into individual instrument components.
Abstract:
A device includes one or more processors configured to provide audio data samples to a sound event classification model. The one or more processors are also configured to determine, based on an output of the sound event classification model responsive to the audio data samples, whether a sound class of with the audio data samples was recognized by the sound event classification model. The one or more processors are further configured to, based on a determination that the sound class was not recognized, determine whether the sound event classification model corresponds to an audio scene associated with the audio data samples. The one or more processors are also configured to, based on a determination that the sound event classification model corresponds to the audio scene associated with the audio data samples, store model update data based on the audio data samples.
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.
Abstract:
An apparatus for detecting a sound in an acoustical environment includes a microphone array configured to detect an audio signal in the acoustical environment. The apparatus also includes a processor configured to determine an angular location of a sound source of the audio signal. The angular location is relative to the microphone array. The processor is also configured to determine at least one reverberation characteristic of the audio signal. The processor is further configured to determine a distance, relative to the microphone array, of the sound source along an axis associated with the angular location based on the at least one reverberation characteristic.
Abstract:
A method of operation of a device includes receiving an input signal at the device. The input signal is generated using at least one microphone. The input signal includes a first signal component having a first amount of wind turbulence noise and a second signal component having a second amount of wind turbulence noise that is greater than the first amount of wind turbulence noise. The method further includes generating, based on the input signal, an output signal at the device. The output signal includes the first signal component and a third signal component that replaces the second signal component. A first frequency response of the input signal corresponds to a second frequency response of the output signal.
Abstract:
An apparatus for detecting a sound in an acoustical environment includes a microphone array configured to detect an audio signal in the acoustical environment. The apparatus also includes a processor configured to determine an angular location of a sound source of the audio signal. The angular location is relative to the microphone array. The processor is also configured to determine at least one reverberation characteristic of the audio signal. The processor is further configured to determine a distance, relative to the microphone array, of the sound source along an axis associated with the angular location based on the at least one reverberation characteristic.
Abstract:
A device includes a memory and a processor. The memory is configured to store a threshold. The processor is configured to authenticate a user based on authentication data. The processor is also configured to, in response to determining that the user is authenticated, generate a correlation score indicating a correlation between a first signal received from a first sensor and a second signal received from a second sensor. The processor is also configured to determine liveness of the user based on a comparison of the correlation score and the threshold.
Abstract:
A method for speech modeling by an electronic device is described. The method includes obtaining a real-time noise reference based on a noisy speech signal. The method also includes obtaining a real-time noise dictionary based on the real-time noise reference. The method further includes obtaining a first speech dictionary and a second speech dictionary. The method additionally includes reducing residual noise based on the real-time noise dictionary and the first speech dictionary to produce a residual noise-suppressed speech signal at a first modeling stage. The method also includes generating a reconstructed speech signal based on the residual noise-suppressed speech signal and the second speech dictionary at a second modeling stage.
Abstract:
A method for detecting voice activity by an electronic device is described. The method includes detecting near end speech based on a near end voiced speech detector and at least one single channel voice activity detector. The near end voiced speech detector is associated with a harmonic statistic based on a speech pitch histogram.
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.