Systems and methods for generating training data are described herein. Pieces of metadata captured by a plurality of networked sensor systems can be captured, where each piece of metadata is associated with a specific set of sensor data captured by one of the plurality of networked sensor systems and includes a set of characteristics for the specific set of captured sensor data. A probabilistic model can be generated based on the received metadata and simulations can be performed based upon a training corpus by generating multiple scenarios, and, for each scenario, a scenario specific version of a particular annotated sample is generated by performing a simulation using the particular annotated sample. The scenario specific versions of annotated samples from the training corpus can be stored as a training data set on the at least one network device.

A device including a speech recognition function which recognizes speech from a user, includes: a loudspeaker which outputs speech to a space; a microphone which collects speech in the space; a first speech recognition unit which recognizes the speech collected by the microphone; a command control unit which issues a command for controlling the device, based on the speech recognized by the first speech recognition unit; and a control unit which prohibits the command issuance unit from issuing the command, based on the speech to be output from the loudspeaker.

Techniques of performing acoustic echo cancellation involve providing a bi-magnitude filtering operation that performs a first filtering operation when a magnitude of an incoming audio signal to be output from a loudspeaker is less than a specified threshold and a second filtering operation when the magnitude of the incoming audio signal is greater than the threshold. The first filtering operation may take the form of a convolution between the incoming audio signal and a first impulse response function. The second filtering operation may take the form of a convolution between a nonlinear function of the incoming audio signal and a second impulse response function. For such a convolution, the bi-magnitude filtering operation involves providing, as the incoming audio signal, samples of the incoming audio signal over a specified window of time. The first and second impulse response functions may be determined from an input signal input into a microphone.

An audio data processing method is provided. The method includes: obtaining multi-path audio data in an environmental space, obtaining a speech data set based on the multi-path audio data, and separately generating, in a plurality of enhancement directions, enhanced speech information corresponding to the speech data set; matching a speech hidden feature in the enhanced speech information with a target matching word, and determining an enhancement direction corresponding to the enhanced speech information having a highest degree of matching with the target matching word as a target audio direction; obtaining speech spectrum features in the enhanced speech information, and obtaining, from the speech spectrum features, a speech spectrum feature in the target audio direction; and performing speech authentication on the speech hidden feature and the speech spectrum feature that are in the target audio direction based on the target matching word, to obtain a target authentication result.

An example method of operation may include identifying, in a particular room environment, a number of speakers and one or more microphones on a network controlled by a controller and amplifier, providing test signals to play sequentially from each amplifier channel of the amplifier and the speakers, monitoring the test signals from the one or more microphones simultaneously to detect operational speakers and amplifier channels, providing additional test signals to the speakers to determine tuning parameters, detecting the additional test signals at the one or more microphones controlled by the controller, and automatically establishing a background noise level and noise spectrum of the room environment based on the detected additional test signals.

A voice controlled assistant has a housing to hold one or more microphones, one or more speakers, and various computing components. The housing has an elongated cylindrical body extending along a center axis between a base end and a top end. The microphone(s) are mounted in the top end and the speaker(s) are mounted proximal to the base end. The microphone(s) and speaker(s) are coaxially aligned along the center axis. The speaker(s) are oriented to output sound directionally toward the base end and opposite to the microphone(s) in the top end. The sound may then be redirected in a radial outward direction from the center axis at the base end so that the sound is output symmetric to, and equidistance from, the microphone(s).

In some embodiments, an echo cancellation method which includes adaptation of at least one prediction filter, with adaptation step size controlled using gradient descent on a set of filter coefficients of the filter, where control of the adaptation step size is based at least in part on a direction of adaptation and a predictability of a gradient of adaptation (e.g., a gradient vector). Other aspects of embodiments of the invention include systems, methods, and computer program products for controlling adaptation step size of adaptive (e.g., low-complexity adaptive) echo cancellation. In some embodiments, adaptation step size control is based on a normalized, scaled gradient of adaptation, or includes smoothing of a normalized gradient of adaptation

This application relates to the field of signal processing technologies and headsets, and provides a speech signal processing method and apparatus, to provide a full-band low-noise speech signal. The method is applied to a headset including at least two speech collectors, where the at least two speech collectors include an ear canal speech collector and at least one external speech collector. The method includes: preprocessing a speech signal that is in a first frequency band and that is collected by the ear canal speech collector, to obtain a first speech signal; preprocessing a speech signal that is in a second frequency band and that is collected by the at least one external speech collector, to obtain an external speech signal, where frequency ranges of the first frequency band and the second frequency band are different; performing correlation processing on the first speech signal and the external speech signal to obtain a second speech signal; and outputting a target speech signal, where the target speech signal includes the first speech signal and the second speech signal.

This application provides a speech signal processing method and apparatus, and relates to the field of signal processing technologies and earphone, to monitor an ambient sound signal and improve a monitoring effect and user experience. The method is applied to an earphone, where the earphone includes at least one external speech collector. The method includes: preprocessing a speech signal collected by the at least one external speech collector, to obtain an external speech signal; extracting an ambient sound signal from the external speech signal; and performing audio mixing processing on a first speech signal and the ambient sound signal based on amplitudes and phases of the first speech signal and the ambient sound signal and a location of the at least one external speech collector, to obtain a target speech signal.

An electronic device for improving a quality of an audio includes: a microphone configured to obtain an audio input including a voice; at least one memory; and at least one processor. The at least one processor is configured to execute one or more instructions stored in the memory to: obtain a first voice fingerprint corresponding to the obtained audio input; obtain a second voice fingerprint corresponding to the voice; estimate, based on the first voice fingerprint and the second voice fingerprint, noise caused by an acoustic environment of the obtained audio input; and remove the estimated noise from the obtained audio input.