An all-analog natural language processing system is provided. Analog audio input is processed directly by an all-analog signal pathway wherein the audio activity detection, voice activity detection, feature extraction and neural network processing are all performed in the analog domain. Audio/voice detection and feature extraction is performed by a bandpass filter bank having a plurality of individual bandpass filters. Each bandpass filter includes an array of individual capacitively coupled current conveyor second order sections having a charge-trap transistor as a programmable element for tuning the passband of the filter. Compared to typical digital systems for natural language processing, the present all-analog system can perform natural language processing with comparable accuracy but greatly reduced energy consumption of up to two orders of magnitude less.

A speech noise reduction processing method, an apparatus, a computer device and a storage medium. The method comprises: responsive to a distance between a speech collection device and a target object being detected to reach a preset value, acquiring a noisy speech signal collected by the speech collection device and performing frequency division processing on the noisy speech signal to obtain a low-frequency band signal; acquiring an amplitude spectrum and a phase spectrum of the low-frequency band signal; acquiring a modulation domain signal corresponding to the amplitude spectrum; performing spectral subtraction to obtain a noise-reduced modulation domain amplitude spectrum; compensating the modulation domain phase spectrum to obtain the compensated modulation domain phase spectrum; and obtaining a noise-reduced low-frequency band signal based on the compensated modulation domain phase spectrum, the noise-reduced modulation domain amplitude spectrum and the phase spectrum of the low-frequency band signal.

A speech noise reduction processing method, an apparatus, a computer device and a storage medium. The method comprises: responsive to a distance between a speech collection device and a target object being detected to reach a preset value, acquiring a noisy speech signal collected by the speech collection device and performing frequency division processing on the noisy speech signal to obtain a low-frequency band signal; acquiring an amplitude spectrum and a phase spectrum of the low-frequency band signal; acquiring a modulation domain signal corresponding to the amplitude spectrum; performing spectral subtraction to obtain a noise-reduced modulation domain amplitude spectrum; compensating the modulation domain phase spectrum to obtain the compensated modulation domain phase spectrum; and obtaining a noise-reduced low-frequency band signal based on the compensated modulation domain phase spectrum, the noise-reduced modulation domain amplitude spectrum and the phase spectrum of the low-frequency band signal.

Introduced here are computer programs and associated computer-implemented techniques for manipulating noisy audio signals to produce clean audio signals that are sufficiently high quality so as to be largely, if not entirely, indistinguishable from “rich” recordings generated by recording studios. When a noisy audio signal is obtained by a media production platform, the noisy audio signal can be manipulated to sound as if recording occurred with sophisticated equipment in a soundproof environment. Manipulation can be performed by a model that, when applied to the noisy audio signal, can manipulate its characteristics so as to emulate the characteristics of clean audio signals that are learned through training.

Introduced here are computer programs and associated computer-implemented techniques for manipulating noisy audio signals to produce clean audio signals that are sufficiently high quality so as to be largely, if not entirely, indistinguishable from “rich” recordings generated by recording studios. When a noisy audio signal is obtained by a media production platform, the noisy audio signal can be manipulated to sound as if recording occurred with sophisticated equipment in a soundproof environment. Manipulation can be performed by a model that, when applied to the noisy audio signal, can manipulate its characteristics so as to emulate the characteristics of clean audio signals that are learned through training.

An electronic device is provided. The electronic device comprises a speaker, a plurality of microphones, at least one processor operatively connected with the speaker and the plurality of microphones, and a memory operatively connected with the at least one processor, wherein the memory is configured to store instructions which, when executed, cause the at least one processor to perform speech audio processing or non-speech audio processing on audio signals received via the plurality of microphones, upon obtaining a non-speech audio signal based on the speech audio processing or the non-speech audio processing, identify a non-speech audio signal pattern corresponding to the non-speech audio signal, obtain a non-speech audio signal-based first command based on the identified non-speech audio signal pattern, and perform at least one action corresponding to the obtained non-speech audio signal-based first command.

An electronic device is provided. The electronic device comprises a speaker, a plurality of microphones, at least one processor operatively connected with the speaker and the plurality of microphones, and a memory operatively connected with the at least one processor, wherein the memory is configured to store instructions which, when executed, cause the at least one processor to perform speech audio processing or non-speech audio processing on audio signals received via the plurality of microphones, upon obtaining a non-speech audio signal based on the speech audio processing or the non-speech audio processing, identify a non-speech audio signal pattern corresponding to the non-speech audio signal, obtain a non-speech audio signal-based first command based on the identified non-speech audio signal pattern, and perform at least one action corresponding to the obtained non-speech audio signal-based first command.

According to certain embodiments, an electronic device comprises a microphone configured to acquire a signal including a voice signal and noise signal; a speaker; a memory; and a processor, wherein the processor is configured to: receive the signal from the microphone, wherein the signal corresponds to a plurality of predetermined frequency bands; identify portions of the signal corresponding to a first band and a second band of the plurality of frequency bands; calculate a signal-to-noise ratio (SNR) values for each predetermined frequency band, based on the signal; obtain a first parameter for correcting the portion of the signal corresponding to the first band and a second parameter for correcting the portion of the signal corresponding to the second band, based on the calculated SNR values for the first band and the second band; and apply the first parameter and the second parameter to each of the predetermined frequency bands.

According to certain embodiments, an electronic device comprises a microphone configured to acquire a signal including a voice signal and noise signal; a speaker; a memory; and a processor, wherein the processor is configured to: receive the signal from the microphone, wherein the signal corresponds to a plurality of predetermined frequency bands; identify portions of the signal corresponding to a first band and a second band of the plurality of frequency bands; calculate a signal-to-noise ratio (SNR) values for each predetermined frequency band, based on the signal; obtain a first parameter for correcting the portion of the signal corresponding to the first band and a second parameter for correcting the portion of the signal corresponding to the second band, based on the calculated SNR values for the first band and the second band; and apply the first parameter and the second parameter to each of the predetermined frequency bands.

Techniques for presence-detection devices to detect movement of a person in an environment by emitting ultrasonic signals using a loudspeaker that is concurrently outputting audible sound. To detect movement by the person, the devices characterize the change in the frequency, or the Doppler shift, of the reflections of the ultrasonic signals off the person caused by the movement of the person. However, when a loudspeaker plays audible sound while emitting the ultrasonic signal, audio signals generated by microphones of the devices include distortions caused by the loudspeaker. These distortions can be interpreted by the presence-detection devices as indicating movement of a person when there is no movement, or as indicating lack of movement when a user is moving. The techniques include processing audio signals to remove distortions to more accurately identify changes in the frequency of the reflections of the ultrasonic signals caused by the movement of the person.