The present invention relates to an active noise cancellation integrated circuit for stacking multiple anti-noise signals, an associated method, and an active noise cancellation headphone using the same. The method is applicable to an audio playback device with multiple ANC filtering units. The method includes: acquiring an anti-noise signal from an ANC filtering unit; generating a decoupled signal by processing the anti-noise signal with the transfer function of a physical channel and operations of other ANC filtering units; performing a signal superposition, wherein an anti-noise signal from another ANC filtering unit is superposed with the decoupled signal; and performing an audio playback based on the superposed signal and an audio signal such that noise is eliminated.

One example method includes performing sound quality operations. Microphone arrays are used to cancel background noise and to enhance speech. With arrays at each environment of each user participating in a call, a first microphone array can cancel or suppress background noise and a second array can generate enhanced speech for transmission to other users. Thus, for user, the audio signal output by the user's device includes an anti-noise signal to cancel background noise present in the user's environment and enhanced speech from other users.

An echo filtering method, an electronic device, a computer-readable storage medium, and an echo filtering apparatus are disclosed. The electronic device includes M microphones and N speakers. M and N are integers greater than 1. The method includes: obtaining N speaker signals corresponding to the N speakers (302); obtaining M microphone signals corresponding to the M microphones (304); and performing at least direct sound filtering on the N speaker signals and the M microphone signals to obtain a target signal (306). By using this method, better echo filtering effect can be obtained.

Systems and methods for audio listening devices, comprise a speaker coupled to a first housing, a sound port having a first end and a second end, wherein the first end is coupled to the first housing, and the second end is configured to be inserted in an ear canal of a person such that sound waves emitted from the speaker propagates via a secondary path to the ear canal through the sound port, active noise cancellation (ANC) components configured to generate anti-noise signals through the micro-speakers to cancel external noise, and a first microphone disposed within the sound port at the second end of the sound port such that the first microphone is configured to detect the anti-noise signal that propagates through the sound port via the secondary path and the external noise that propagates via a primary path.

Example techniques involve noise-robust acoustic echo cancellation. An example implementation may involve causing one or more speakers of the playback device to play back audio content and while the audio content is playing back, capturing, via the one or more microphones, audio within an acoustic environment that includes the audio playback. The example implementation may involve determining measured and reference signals in the STFT domain. During each n.sup.th iteration of an acoustic echo canceller (AEC): the implementation may involve determining a frame of an output signal by generating a frame of a model signal by passing a frame of the reference signal through an instance of an adaptive filter and then redacting the n.sup.th frame of the model signal from an n.sup.th frame of the measured signal. The implementation may further involve determining an instance of the adaptive filter for a next iteration of the AEC.

A system and method for mitigating audio feedback may calculate a smoothed frequency spectrum of an audio signal. Previously detected candidate feedback tones may be obtained. Candidate feedback tones may be determined responsive to a frequency spectrum of the audio signal, the smoothed frequency spectrum and the previously detected candidate feedback tones. One or more signal characteristics associated with the audio signal and feedback coefficients associated with the candidate feedback tones may be obtained. The feedback coefficients may be modified responsive to the one or more signal characteristics. Actionable feedback tones may be determined responsive to the associated feedback coefficients exceeding a respective feedback threshold. Feedback suppression coefficients associated with each of the determined actionable feedback tones may be generated and may be utilized to suppress the actionable feedback tones.

A method of echo path delay destination and echo cancellation is described in this disclosure. The method includes: obtaining a reference signal, a microphone signal, and a trained multi-task deep neural network, wherein the multi-task deep neural network comprises a first neural network and a second neural network; generating, using the first neural network of the multi-task deep neural network, an estimated echo path delay based on the reference signal and the microphone signal; updating the reference signal based on the estimated echo path delay; and generating, using the second neural network of the multi-task deep neural network, an enhanced microphone signal based on the microphone signal and the updated reference signal.

Embodiments include an audio system comprising a speaker array comprising a plurality of drivers arranged in a first planar configuration; a microphone array comprising a plurality of transducers arranged in a second planar configuration; and a beamformer communicatively coupled to the speaker array and the microphone array, the beamformer configured to: generate an individual speaker output signal for each of the drivers in the speaker array based on one or more input audio signals received from an audio source, and generate a microphone output signal for the microphone array based on one or more microphone signals captured by one or more of the transducers. Embodiments also include a method performed by one or more processors coupled to a microphone array having a plurality of transducers and a speaker array having a plurality of drivers.

An acoustic echo canceller (AEC) uses a simulated echo from an adaptive filter to cancel an actual echo from a real environment. The echo cancellation is optimal when the adaptive filter response accurately matches the environment response. This can be achieved by changing coefficients of the filter in a step-wise fashion until the filter is converged on a configuration that provides optimal results. The convergence of the filter can be negatively affected by interference due to a double talk event or by an event in which the environment is changed. The disclosed AEC is configured to respond to these disruptive events by adjusting a step-size of the adaptive algorithm used to change the coefficients.

By using the adaptive filter, the reference input signal is processed so as to identify a pseudo-signal of a particular signal to be deleted. The pseudo-signal is subtracted from the mixture containing a target signal inputted from a microphone, the particular signal to be deleted, and a noise so as to obtain an error signal. A stationary noise is estimated to obtain a stationary noise estimated value. A non-stationary noise is estimated to obtain a non-stationary noise estimated value. The stationary noise estimated value is mixed with the non-stationary estimated value to obtain a mixed noise estimated value. An update amount is calculated according to a correlation value between the error signal and the reference input signal, and the mixed noise estimated value. According to the update amount, a coefficient of the adaptive filter is updated.