Hi-Fi tone quality identifying method based on pattern recognition

Abstract

The invention discloses a Hi-Fi tone quality identifying method based on pattern recognition. The method includes the steps: selecting a learning sample, converting a sample time domain signal into a frequency domain signal, and making a frequency attenuation mean value every 500Hz from 11050Hz to 22050Hz serve as a characteristic, wherein twenty two characteristics are provided and numbered from one to twenty two. Through statistical learning of a lot of already labeled lossy and lossless audios, a lossless audio condition probability corresponding to a lossless audio characteristic is obtained, a lossy audio condition probability corresponding to a lossy audio characteristic is obtained, Fourier transform is performed for a to-be-measured audio, and a combined probability can be calculated and then the probability of the specific tone quality of a given audio can be reckoned after condition probabilities between the characteristics and between the characteristics and the tone quality are obtained by extracting the frequency characteristics. Through the above algorithm, a high detection success rate of real lossless audios is achieved, and a relatively low misjudgement rate of false lossless audios is guaranteed. Moreover, compared with auCDtect, the method can reach the advanced level in the industry.

Description

technical field [0001] The invention relates to audio signal processing and, in particular, to a Hi-Fi sound quality detection method based on pattern recognition. Background technique [0002] Hi-Fi audio refers to the original CD audio. This type of audio is produced by major record companies, etc., using professional recording and reverberation equipment to sample and quantify the original sound information, and has not undergone spectrum clipping, so the original frequency bands are retained. Information. [0003] With the rapid popularization of the Internet and the increase of bandwidth, people's requirements for music quality are getting higher and higher, and the exchange of lossless music resources is also transitioning from music enthusiasts to the general public. But how to identify the authenticity of such resources, music lovers and music companies have an urgent need. Although manual detection has a high accuracy rate, it is only applicable to individuals. Fo...

AI Technical Summary

Problems solved by technology

For example, some compression algorithms, in order to reduce the volume of the audio, after the original audio is compressed by the algorithm, the high-frequency information is missing

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