Music retrieval system based on audio fingerprint features

Abstract

The invention belongs to the technical field of information retrieval, and particularly relates to a music retrieval system based on audio fingerprint features. The system is composed of a preprocessing module, a feature extraction module, a reverse index module and a fine matching module. The preprocessing module mainly carries out audio signal conversion, resampling and filtering; the feature extraction module is used for representing audio files, wherein the audio fingerprint features are adopted to select the most stable point from a frequency spectrum as the feature point through twice screening based on dynamic threshold values, and each feature is represented by a dot pair; according to the reverse index module, the features are used as key words, reverse indexes are built according to the features of a song library, and the index result is returned according to the number of the same key words; according to the fine matching module, the sequential relationship of the audio features is combined, an improved editing distance is adopted as the similarity of two feature sequences, and therefore the index result is optimized. The music retrieval system based on the audio fingerprint features is suitable for the retrieval of a large number of songs, and can particularly conduct effective retrieval on record inquiry segments.

Description

technical field [0001] The invention belongs to the technical field of information retrieval, specifically relates to audio signal processing and multimedia information retrieval systems, and further relates to a music retrieval system based on audio fingerprint features. Background technique [0002] Earlier, since music information was unstructured data, its retrieval system generally implemented retrieval based on text description. For example, to retrieve a song in the Internet, search by the name of the song, singer, songwriter, song access format, etc. This method has many disadvantages: the amount of data is getting larger and larger, so the workload of manual annotation is also increasing; audio perception is difficult to express clearly with text annotation; information description has a certain degree of subjectivity. The content-based music retrieval system retrieves the content according to the characteristic parameters of the information itself rather than the ...

AI Technical Summary

Problems solved by technology

This method has many disadvantages: the amount of data is increasing, and the workload of manual annotation is also increasing; audio perception is difficult to express clearly with text annotation; information description has a certain degree of subjectivity

In the case of massive music data, there will be many hash conflicts and it is not applicable. At the same time, the feature performance is not as good as the previous fingerprint feature.

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