An Audio Retrieval Method Based on Chromagram and Distance Metrics
In this paper, a content-based audio retrieval method is proposed, which can quickly detect and locate similar sound in audio database. We extract a chroma-based audio feature: chromagram, a variation on time-frequency distributions, which represents the spectral energy at each of 12 pitch classes. Compared with traditional feature MFCC (Mel Frequency Cesptral Coefficient), chromagram is better when using correlation distance as audio similarity measurement. Then we choose Jonathan Foote’s music retrieval database to do experiments and final results show that the retrieval accuracy can reach over 96.7％ using chromagram as features even when the signal-tonoise ratio is 0 dB.
Xiaoqing Yu Jing Zhang Junwei Liu Wanggen Wan Wei Yang
School of Communication and Information Engineering, Shanghai University Shanghai 20072, China
国际会议
上海
英文
425-428
2010-10-20（万方平台首次上网日期，不代表论文的发表时间）