A method and a device for audio repair and a readable storage medium are provided. The method includes the following. Multiple audio frames are sequentially inputted into a cache module, where the cache module is sequentially composed of multiple processing units, and a processing unit located at a center of the multiple processing units is a center processing unit (201). At least one audio frame contained in the center processing unit is assigned as a target frame (202). A noise point presented as a short-term high-energy pulse in the target frame is detected according to audio characteristics of the multiple audio frames in the cache module (203). The target frame is repaired to remove the noise point in the target frame (204).

Disclosed in the invention are an in-vehicle intelligent WiFi microphone and an audio delay processing method therefor, by which the problem that the existing in-vehicle microphone is prone to interference and provides poor sound quality when FM signals are used to establish audio transmission with an in-vehicle entertainment system, can be solved. The in-vehicle intelligent WiFi microphone comprises a first microphone, a first main control circuit board, a first rechargeable battery and a first main mounting housing. The first microphone, the first main control circuit board and the first rechargeable battery are arranged in the first main mounting housing. The first microphone is located at an upper end of the first main mounting housing, and the first microphone and the first rechargeable battery are electrically connected to the first main control circuit board. The first main control circuit board is integrally provided with a first main control processor, as well as an audio mixing processing module, an FM receiving module and a WiFi communication module, which are electrically connected to the first main control processor.

According to an aspect, a method for multi-channel echo cancellation includes receiving a microphone signal and a multi-channel loudspeaker driving signal. The multi-channel loudspeaker driving signal includes a first driving signal that drives a first loudspeaker, and a second driving signal that drives a second loudspeaker. The first driving signal is substantially the same as second driving signal. The microphone signal includes a near-end signal with echo. The method includes determining a unique solution for acoustic transfer functions for a present acoustic scenario based on the microphone signal and the multi-channel loudspeaker driving signal. The acoustic transfer functions include first and second acoustic transfer function. The unique solution is determined based on time-frequency transforms of observations from the present acoustic scenario and at least one previous acoustic scenario. The method includes removing the echo from the microphone signal based on the first and second acoustic transfer function.

Various technologies described herein pertain to active noise cancellation in the interior of a vehicle. In exemplary embodiments, a microphone mounted on the vehicle outputs an audio signal indicative of noise emitted by a noise source. A computing system of the vehicle determines a position of the noise source based upon sensor signals output by sensors mounted on the vehicle. The computing system further determines a position of a passenger in the vehicle based upon a sensor mounted inside the vehicle. The computing system generates a complementary signal that is configured to attenuate the noise based upon the audio signal, the position of the noise source, and the position of the passenger. The complementary signal is then output by way of a speaker in the interior of the vehicle.

Dynamic device speaker tuning for echo control includes detecting audio rendering from a speaker on a device; based at least on detecting the audio rendering, capturing, with a microphone on the device, an echo of the rendered audio; performing a Fourier Transform on the echo and the rendered audio; determining a real-time transfer function for at least one signature band; determining a difference between the real-time transfer function and a reference transfer function; and tuning the speaker for audio rendering, based at least on the difference between the real-time transfer function and the reference transfer function, by adjusting an audio amplifier equalization. For some examples, the signature band represents a wall echo or an alternative mounting option. For some examples, the echo is collected during intervals while the audio rendering is ongoing.

System and method for detecting and identifying noises in a sound signal occurring during a call on a mobile device and selectively filtering and suppressing the noises in the sound signal are provided. In the mobile device, a processor is configured to receive a sound signal, detect noises in the received sound signal, identify the noises in the received sound signal, display the identified noises in a user interface (UI), receive a selection of the displayed identified noises from the UI, and filter the received selection of the displayed identified noises from the received sound signal. The processor may use a machine learning module with a neural network to detect and identify the noises in the received sound signal.

Methods, apparatus, systems, and articles of manufacture are disclosed to enhance and audio signal. An example apparatus includes processor circuitry to at least determine a first signal spectrum corresponding to a first microphone, the first signal spectrum identifying first audio, determine a second signal spectrum corresponding to a second microphone, the second signal spectrum identifying the first audio, the second spectrum different from the first spectrum, the first microphone different from the second microphone, the second signal spectrum having a first spectral distance to the first signal spectrum, calculate a mask based on the first and second signal spectrums, and generate a third signal spectrum corresponding to the first microphone utilizing the mask and the first signal spectrum, the third signal spectrum different from the first signal spectrum, the third signal spectrum having a second spectral distance to the second signal spectrum, the second spectral distance less than the first spectral distance.

A multi-stage noise suppression system for reducing noise components in a noisy input signal has a first stage neural network that estimates a noise power spectrum for the noisy input signal. A first set of gain values corresponding to the noise power spectrum is generated by the first stage neural network. A second stage neural network estimates clean signal power spectrum values, which are derived from an application of a second set of gain values generated as a function of the clean signal power spectrum values and a first stage reduced noise signal power spectrum values.

The disclosure describes one or more embodiments of an acoustic improvement system that accurately and efficiently determines and provides actionable acoustic improvement suggestions to users for digital audio recordings via an interactive graphical user interface. For example, the acoustic improvement system can assist users in creating high-quality digital audio recordings by providing a combination of acoustic quality metrics and actionable acoustic improvement suggestions within the interactive graphical user interface customized to each digital audio recording. In this manner, all users can easily and intuitively utilize the acoustic improvement system to improve the quality of digital audio recordings.

Embodiments allow for an auto-mixer to gate microphones on and off based on speech detection, without losing or discarding the speech received during the speech recognition period. An example method includes receiving and storing an input audio signal. The method also includes determining, based on a first segment of the input audio signal, that the input audio signal comprises speech, and determining a delay between the input audio signal and a corresponding output audio signal provided to a speaker. The method also includes reducing the delay, wherein reducing the delay comprises removing one or more segments of the stored input audio signal to create a time-compressed audio signal and providing the time-compressed audio signal as the corresponding output audio signal. The method also includes determining that the delay is less than a threshold duration, and responsively providing the input audio signal as the corresponding output audio signal.