A feature independent of bit rate for twinvq audio retrieval

In this paper we propose an audio feature for TwinVQ audio retrieval. For making effective audio database, we consider that these two techniques (compression and feature extraction) are dealt with on one platform. The proposed audio feature satisfies the following requirements: 1) independent of bit rate; 2) extractable from compressed data without decoding; 3) computable in the framework of TwinVQ. We show that the autocorrelation coefficient is theoretically independent of bit rate and confirm experimentally that the feature computed from CD audio data is actually independent of bit rate.