Disclosed are systems and methods for a frontend capture module of a video conferencing application, which can modify an input signal, received from a microphone device to match predetermined signal characteristics, such as voice signal level and expected noise floor. An Input stage, a suppression module and an output stage amplify the voice signal portion of the input signal and suppress the noise signal of input signal to predetermined ranges. The input stage selectively applies gains defined by a gain table, based on signal level of the input signal. The suppression module selectively applies a suppression gain to the input signal based on presence or absence of voice signal in the input signal. The output stage further amplifies the input signal in portions having a voice signal and applies a gain table to maintain a consistent noise floor.

Methods and systems for determining periods of excessive noise for smart speaker voice commands. An electronic timeline of volume levels of currently playing content is made available to a smart speaker. From this timeline, periods of high content volume are determined, and the smart speaker alerts users during periods of high volume, requesting that they wait until the high-volume period has passed before issuing voice commands. In this manner, the smart speaker helps prevent voice commands that may not be detected, or may be detected inaccurately, due to the noise of the content currently being played.

In a method for coding of information for enhancing a background noise representation, voice activity of an input speech signal is determined. A noisiness parameter is determined for an inactive speech signal, wherein the noisiness parameter is based on a ratio of prediction gains of two Linear Predictive Coder (LPC) prediction filters with different orders. The noisiness parameter is quantized, and the quantized noisiness parameter is encoded for transmission.

A voice processing apparatus calculates a phase difference between first and second frequency signals obtained by transforming first and second voice signals generated by two voice input units for each frequency, calculates, for each extension range set outside or inside a reference range, a presence ratio based on the number of frequencies with the phase difference between the first and second frequency signals falling within the extension range, the reference range representing a range of the phase difference between the first and second voice signals for each frequency and corresponding to a direction in which a target sound source is assumed to be located, and sets, as a non-suppression range, a first extension range having the presence ratio higher than a predetermined value and a second extension range closer to the phase difference at the center of the reference range than the first extension range is within the reference range.

A high-performance method evaluates a useful signal of an audio device, and in particular of an audio apparatus, for example for reducing interference. Accordingly, in the method at least two microphone signals are each obtained from a sound signal and a reference signal is obtained from the microphone signals, a portion of the microphone signals from a predetermined direction being blocked. The microphone signals are filtered by a filter such that an evaluation signal is obtained. To that end, a coherence value is determined from portions of the reference signal and a power density value is determined from the coherence value. The filter is parameterized on the basis of the power density value.

A method of processing an audio signal includes determining an average signal-to-noise ratio for the audio signal over time. The method includes, based on the determined average signal-to-noise ratio, a formant-sharpening factor is determined. The method also includes applying a filter that is based on the determined formant-sharpening factor to a codebook vector that is based on information from the audio signal.

Methods and systems for providing consistency in noise reduction during speech and non-speech periods are provided. First and second signals are received. The first signal includes at least a voice component. The second signal includes at least the voice component modified by human tissue of a user. First and second weights may be assigned per subband to the first and second signals, respectively. The first and second signals are processed to obtain respective first and second full-band power estimates. During periods when the user's speech is not present, the first weight and the second weight are adjusted based at least partially on the first full-band power estimate and the second full-band power estimate. The first and second signals are blended based on the adjusted weights to generate an enhanced voice signal. The second signal may be aligned with the first signal prior to the blending.

A method of noise reduction includes using a neural network to control a Wiener filter. The gains estimated by the neural network are combined with the gains produced by the Wiener filter. In this manner, the noise reduction system provides improved results as compared to using only a neural network.

Disclosed are methods, systems, device, and other implementations, including a method that includes receiving an audio signal representation, detecting in the received audio signal representation, using a first learning model, one or more silent intervals with reduced foreground sound levels, determining based on the detected one or more silent intervals an estimated full noise profile corresponding to the audio signal representation, and generating with a second learning model, based on the received audio signal representation and on the determined estimated full noise profile, a resultant audio signal representation with a reduced noise level.

Methods and systems for determining periods of excessive noise for smart speaker voice commands. An electronic timeline of volume levels of currently playing content is made available to a smart speaker. From this timeline, periods of high content volume are determined, and the smart speaker alerts users during periods of high volume, requesting that they wait until the high-volume period has passed before issuing voice commands. In this manner, the smart speaker helps prevent voice commands that may not be detected, or may be detected inaccurately, due to the noise of the content currently being played.