Audio Similarity Measure Based on Renyi’s Quadratic Entropy
Considering noise interference often exists in audio processing, it is not robust enough to calculate audio similarity by using distance measure directly. In this paper, basing on Renyi’s quadratic entropy,a novel scheme for audio similarity measure is proposed. In our work, we extract Mel Frequency Cepstral Coefficients (MFCCs) to represent each audio, and then calculate the similarity based on the entropy of audio samples by probability density function (pdf) of MFCCs which can be estimated by Parzen window. The experimental results show that: (a) our approach has better performance than the one based on Euclidean distance in the common SNR condition, (b) our approach can achieve 94.00％ matching accuracy even when the signal to noise ratio (SNR) is 0db. In addition, our algorithm also can be applied in audio retrieval and musical cluster.
Xiaoqing Yu Xueqian Pan Wei Yang Wanggen Wan Jing Zhang
School of Communication and Information Engineering, Shanghai University Shanghai 200072, China
国际会议
上海
英文
722-726
2010-10-20（万方平台首次上网日期，不代表论文的发表时间）