Massive digital audio fingerprint storage and retrieval method

Abstract

The invention discloses a massive digital audio fingerprint storage and retrieval method, which comprises two steps of digital audio fingerprint storage and digital audio fingerprint retrieval, and the digital audio fingerprint storage comprises the following steps of: performing Hash processing on an audio file to be stored to obtain a unique identifier of each audio file; extracting audio fingerprints of the audio files to be stored, wherein the audio fingerprint of each audio file forms a character string; taking an identifier obtained after Hash of each to-be-processed audio file as a Rowkey of the Hbase, taking the fingerprint character string as a value of one column, taking meta information as a value of the other column, writing the values into a table of the Hbase, and writing thevalues into the Hbase; and taking identifier and fingerprint character string obtained after Hash of each audio file to be processed as two fields of document corresponding to audio file to be processed, and writing two fields into ES. Near-real-time full-text search and distributed characteristics of ES are utilized, and concurrent and real-time query is supported while high-efficiency query isguaranteed.

Description

technical field [0001] The invention belongs to the technical field of music identification query and retrieval, and in particular relates to a method and system for storing and retrieving mass digital audio fingerprints. Background technique [0002] At present, the applications of music recognition include listening to songs, humming, broadcast stream copyright monitoring, car music recognition, video BGM copyright identification, etc. The core of these applications is to extract unique audio features to form special fingerprints, Then compare the extracted fingerprint with the fingerprint of the music in the music library. In the above scenarios that require high accuracy, it is necessary to retain as many fingerprints as possible for comparison. The fingerprints extracted from such a piece of music with an ordinary duration may have nearly 10,000 or tens of thousands of fingerprints. When the music library reaches a large order of magnitude At that time, the number of f...

AI Technical Summary

Problems solved by technology

But music fingerprints are more complex than search engines

The main reason is that the fingerprint library has the same order of magnitude as the search word library, and thousands of fingerprints need to be retrieved for a single match, which also means that one search is equivalent to tens of thousands of searches by the search engine, which limits the method. It can only be applied to a single machine and the database cannot be too large

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