Deep-learning-based audio tone quality enhancement

Abstract

The invention provides a deep-learning-based audio tone quality enhancement method, device, and system, a storage medium and a computer program. The method comprises: acquiring lossy audio data and performing feature extraction on the lossy audio data to obtain features of the lossy audio data; and on the basis of the features of the lossy audio data, reconstructing the lossy audio data by using atrained audio reconstruction neural network to form output audio data with the tone quality close to lossless audio data. According to the invention, the lossy audio tone quality is enhanced based ondeep learning and thus the lossy audio tone quality is close to the tone quality of the lossless audio data by deep neural network reconstruction, so that the tone quality improvement effect that cannot be realized by the traditional method is realized.

Description

technical field [0001] The present invention relates to the technical field of sound quality optimization, and more particularly relates to a deep learning-based audio sound quality enhancement method, device, system, storage medium and computer program. Background technique [0002] Sound quality usually refers to people's subjective evaluation of audio quality. There are many factors that affect the sound quality of audio. For encoded audio, a decisive factor is the degree of audio encoding compression. After the original sound is recorded, it may be a linear pulse code modulation (LPCM) format file, which is a pulse sequence after digital-to-analog conversion. In audio theory, this is the digital audio with the best sound quality and the actual scene. It is a high bit rate lossless format. However, due to the limitations of communication bandwidth and storage space, audio stored on digital devices generally needs to be encoded and compressed. Lossless compression, such...

AI Technical Summary

Problems solved by technology

However, at present, there is no corresponding feasible solution for lossy audio reconstruction using software methods. For the reconstruction of lossy audio, the method of filling or interpolating data is usually adopted, but this method is too rough to restore the sound quality of lossless audio.

Images