Method and System for avoiding howling disturbance especially on conferences, wherein the method comprising the steps of using a howling detector unit implemented inside a multipoint control unit to receive an audio stream input from a client, analyzing the audio input with the howling detector in order to verify if howling noise is present, using at least two of a skewness analysis, a flatness analysis, a crest analysis, a rolloff analysis and preventing the audio stream input to be forwarded as an output to an audio mixer, if howling noise is present.

A public address system includes audio inputs from a moderator/presenter and from one or more participants. In an embodiment, the moderator speaks first and then selects participants to speak, utilizing audio captured by participant devices. A central signal processor is configured to receive the audio inputs and to utilize a configured acoustic model to provide for acoustic echo cancellation (AEC) and feedback control (FBC) during various phases of a presentation or conference. Audio signals from the presenter and/or participants, that have been processed to remove echo, are utilized as reference signals during various phases of the audio presentation that utilize the acoustic model for either AEC or FBC. The system utilizes the knowledge that the best learning occurs during the far talking state to learn the echo path in the canceler mode (AEC) vs. the feedback mode (FBC), which usually can only train in a double-talking mode.

Provided in the present disclosure are a voice processing method, an apparatus, an electronic device, and a storage medium, the method comprising: detecting the working state of a current call system, and when the working state is a two-end speaking state or a remote-end speaking state, performing compression processing on a subsequent remote-end voice signal, acquiring a near-end voice signal by means of a microphone, performing echo processing on the basis of the near-end voice signal and the compression-processed remote-end voice signal to obtain an echo-processed near-end voice signal and a remaining echo signal, performing non-linear suppression processing on the near-end voice signal and the remaining echo signal, and performing gain control on the suppression-processed near-end voice signal.

An electronic device includes sensors configured to detect an orientation of a display, driver logic, and a speaker array. The driver logic processes the audio data received by an interface to form audio output data, and forms driver signals representing the audio output data based on the orientation of the display detected by the one or more sensors. The speaker array receives the driver signals formed orientation of the display, and renders the audio output data for playback based on the driver signals.

Systems and methods are disclosed for audio group identification for conferencing. For example, methods may include joining a conference call using a network interface; accessing an audio signal that has been captured using a microphone; detecting a control signal in the audio signal; and, responsive to detection of the control signal, invoking modification of an audio path of the conference call.

A method and apparatus for processing a signal. An implementation of the method includes: acquiring a reference signal of a to-be-tested voice, the reference signal being a signal output to a voice output device, where the voice output device outputs the to-be-tested voice after obtaining the reference signal; receiving, from a voice input device, an echo signal of the to-be-tested voice, the echo signal being a signal of the to-be-tested voice collected by the voice input device; performing signal preprocessing on the reference signal and the echo signal respectively; and inputting the processed reference signal and the processed echo signal into a pre-trained time delay estimation model, to obtain a time difference between the reference signal and the echo signal output by the time delay estimation model.

Some implementations involve receiving a content stream that includes audio data, receiving at least one type of level adjustment indication relating to playback of the audio data and controlling a level of the input audio data, based on the at least one type of level adjustment indication, to produce level-adjusted audio data. Some examples involve determining, based at least in part on the type(s) of level adjustment indication, a multiband limiter configuration, applying the multiband limiter to the level-adjusted audio data, to produce multiband limited audio data and providing the multiband limited audio data to one or more audio reproduction transducers of an audio environment.

A control unit of a telephone device is configured to perform a first processing of: estimating a line echo amount based on a volume of a DTMF signal generated by a DTMF signal generation unit and a volume of the DTMF signal input from a line; calculating a howling noise threshold value based on the maximum value of the acoustic echo generated at a handset that is measured in advance and set values of a sidetone volume, a transmission volume, and a reception volume; and calculating a difference between the line echo amount and the howling noise threshold value as an adjustment requisite amount and lowering the set value of the sidetone volume by the adjustment requisite amount when the line echo amount is larger than the howling noise threshold value.

An communication system supports communication paths within an environment by receiving speech signals of a speaker and playing it back for one or more listeners. Signal processing tasks are split into a microphone related part and into a loudspeaker related part. A sound processing system suitable for use in an environment having multiple acoustic zones includes a plurality of microphone communication instances coupled and a plurality of loudspeaker instances.

Methods, systems, and apparatus, including computer programs encoded on computer storage media for acoustic echo cancellation and suppression are provided. An exemplary method comprises receiving a far-end acoustic signal and a corrupted near-end acoustic signal, wherein the corrupted near-end acoustic signal is generated based on (1) an echo of the far-end acoustic signal and (2) a near-end acoustic signal; feeding the far-end acoustic signal and the corrupted near-end acoustic signal into a neural network as an input to output a time-frequency (TF) mask that suppresses the echo and retains the near-end acoustic signal, and generating an enhanced version of the corrupted near-end acoustic signal by applying the obtained TF mask to the corrupted near-end acoustic signal.