The present disclosure provides systems and method for determining a background noise level. The device may receive audio from two or more microphones. The audio may include a first signal and a second signal, such that each microphone receives its own signal. The time, loudness, frequency of the first and second signals may be compared to determine the source of the audio, such as whether the audio is the user's voice or background noise. Based on the source of the audio, the audio may be suppressed to reduce false estimations when calculating the background noise level.

Systems, apparatuses, and methods are described to increase a signal-to-noise ratio difference between a main channel and reference channel. The increased signal-to-noise ratio difference is accomplished with an adaptive threshold for a desired voice activity detector (DVAD) and shaping filters. The DVAD includes averaging an output signal of a reference microphone channel to provide an estimated average background noise level. A threshold value is selected from a plurality of threshold values based on the estimated average background noise level. The threshold value is used to detect desired voice activity on a main microphone channel.

Acoustic Voice Activity Detection (AVAD) methods and systems are described. The AVAD methods and systems, including corresponding algorithms or programs, use microphones to generate virtual directional microphones which have very similar noise responses and very dissimilar speech responses. The ratio of the energies of the virtual microphones is then calculated over a given window size and the ratio can then be used with a variety of methods to generate a VAD signal. The virtual microphones can be constructed using either an adaptive or a fixed filter.

An audio feedback detection apparatus including: a first audio signal input unit configured to acquire a first audio signal collected by a microphone; a second audio signal input unit configured to acquire a second audio signal from an audio communication application to be output to a speaker; and an audio feedback determination unit configured to determine whether an audio feedback is present based on a correlation between a frequency characteristic of the first audio signal input to the audio communication application and a frequency characteristic of the second audio signal input to the speaker. One of the microphone and the speaker is located on a path in which the audio feedback occurs, and the other of the microphone and the speaker is located on a path in which the audio feedback does not occur.

In some aspects, an edge appliance is placed in an active mode and causes a software agent that is based on a machine learning algorithm to engage in a conversation to take an order from a customer that is located at an order post. The edge appliance provides, using a communication interface, audio data that includes the conversation, to a communications system of a restaurant. The edge appliance provides, using the communication interface, a content of a cart associated with the order to a point-of-sale terminal of the restaurant. If the edge appliance determines, using the communication interface, that a microphone of the communication system is receiving audio input from an employee, the edge appliance automatically transitions the edge appliance from the active mode to an override mode, enabling the employee to receive a remainder of the order from the customer.

A communication system with a noise cancellation (NC) assembly providing adaptive or dynamic noise cancellation. The NC assembly includes a localizer module determining, during a communication session (active speaking or during idle times), a location of the active talker. The NC assembly includes a beam generator forming a beam in the determined direction of the active talker to enhance the active talker speech. Once the NC assembly has determined the position of the active talker, the NC assembly assigns a microphone of the microphone array or generated beam in that active direction to be the “active signal” source. The NC assembly assigns a second microphone or beam to be the noise source for NC purposes, and this source may be selected to be in acoustic shadow of the first microphone used as the active signal source or may be the farthest away in its position from the active talker's position.

An embodiment of this application provides a speech processing method and apparatus, and an apparatus for speech processing, applied to a terminal device, where the terminal device is equipped with at least two microphones. The method includes: performing summation on signals received by the at least two microphones to obtain a first signal, and performing subtraction on the signals received by the at least two microphones to obtain a second signal; performing blind separation on the first signal and the second signal to obtain a speech signal and a noise signal; and performing adaptive noise cancellation on the speech signal based on the noise signal to obtain a target speech signal. The embodiments of this application can optimize a speech denoising effect, and further improve the speech recognition accuracy of the terminal device in a complex and changeable environment with large noise or strong interference.

To input the voice of the passenger of a vehicle and output a piece of high-quality enhanced speech independently of the direction of a piece of speech or noise, a speech processing apparatus includes a first microphone that is provided on one of a ceiling member in a vehicle and an accessory thereof, inputs a sound mixture including a voice of a passenger of the vehicle and noise in the vehicle, and outputs a first signal, a second microphone that is provided on one of the ceiling member in the vehicle and the accessory thereof at a position farther than the first microphone when viewed from the passenger of the vehicle, inputs the noise in the vehicle while insulating the voice of the passenger of the vehicle using one of the ceiling member of the vehicle and the accessory thereof, and outputs a second signal, and a noise suppressor that outputs an enhanced speech signal based on the first signal and the second signal.

A system for wind noise suppression is disclosed. The system comprising a first and a second primary microphone configured to generate a first and a second primary electric signal indicative of a first and second primary audio signal, respectively. The system further comprises a secondary detector configured to generate a first secondary electric signal indicative of a secondary audio signal. The system comprises a signal processor comprising a wind strength module configured to determine a wind strength, based on the first primary electric signal and the second primary electric signal, a wind noise module configured to determine a noise estimate, based on the wind strength, and a noise reduction module configured to process the first secondary electric signal to generate a noise-suppressed secondary signal, based on the determined noise estimate.

Systems and methods for enhancing a headset user’s own voice include at least two outside microphones, an inside microphone, audio input components operable to receive and process the microphone signals, a voice activity detector operable to detect speech presence and absence in the received and/or processed signals, and a cross-over module configured to generate an enhanced voice signal. The audio processing components includes a low frequency branch comprising low pass filter banks, a low frequency spatial filter, a low frequency spectral filter and an equalizer, and a high frequency branch comprising highpass filter banks, a high frequency spatial filter, and a high frequency spectral filter.