Index Compression for Audio Fingerprinting Systems Based on Compressed Suffix Array

Abstract

 Abstract—As one of most popular technologies, audio fingerprinting has recently attracted much attention in music retrieval systems. In music retrieval methods based on audio fingerprints, a large database is required in order to compare the fingerprints extracted from the query. In other words, the efficient search method has to be developed. In this paper, we propose a method for index compression using a compressed suffix array. Taking advantage of the fact that the repetitive characters occur frequently in higher bits of the sorted audio fingerprint data, the proposed method compresses the index by encoding the 8-bit data sequences by Run Length Encoding. Vertical Code is also used to compress the array, wherein the positions of the sorted data are stored. Four sets of music databases are used in experiments to evaluate the effectiveness of the proposed method. The experimental results show that the proposed method, compared with the conventional method, only needs 30% of the space of an audio fingerprints database for a music database consisting of 8000 songs, and around 80% of the index space for a database of 1000 songs. Moreover, the entire space cost is reduced to around 60%, compared with the method based on the suffix array. using a suffix array (6) has also been proposed. In the method based on the suffix array, the space cost increases in proportion to the growing music database. In this paper, we proposed a method to reduce the space cost by compressing the index of the database. The paper is organized as follows: Section II outlines music retrieval based on audio fingerprints. We review a fast Hamming space search method (7) based on a suffix array in Section III, and propose a space-saving method based on a compressed suffix array in Section IV. We evaluate the proposed method in Section V. Finally, the conclusions and future work are given in Section VI.