文献类型：期刊文献

英文题名：Robust audio fingerprinting based on GammaChirp frequency cepstral coefficients and chroma

作者：Chen, N.[1];Xiao, H. D.[2];Zhu, J.[3]

机构：[1]E China Univ Sci & Technol, Sch Informat Sci & Technol, Shanghai 200237, Peoples R China;[2]Chinese Acad Sci, Shanghai Adv Res Inst, Shanghai 201210, Peoples R China;[3]Shanghai Jiao Tong Univ, Dept Elect Engn, Shanghai 200240, Peoples R China

年份：2014

卷号：50

期号：4

起止页码：241

外文期刊名：ELECTRONICS LETTERS

收录：;EI(收录号：20140917382429);WOS:【SCI-EXPANDED(收录号:WOS:000331405200003)】；

基金：This work is supported by the National Natural Science Foundation of China (61271349), the Fundamental Research Funds for the Central Universities (WH1214015), the Natural Science Foundation of Shanghai (12ZR1415200), and the China Open Funds of the Shanghai Key Laboratory of Information Security Management Technologies (AGK2012008).

语种：英文

外文关键词：Non-negative matrix factorization - Speech recognition - Audio acoustics - Filter banks - Music

摘要：A novel auditory feature that combines an auditory model and music theory is proposed for audio fingerprinting. First, the input audio is filtered by a GammaChirp (GC) filterbank to model the cochlear frequency selectivity. Then, the output of the filterbank is downsampled and decorrelated by a discrete cosine transform to obtain the GammaChirp frequency cepstral coefficients (GCFCCs). Next, some lowest order GCFCCs are projected onto the chroma to characterise both melodic and harmonic information of the input. Finally, non-negative matrix factorisation is applied to the chroma matrix to reduce its dimension while maintaining its discriminative power. The experimental results illustrate that the proposed scheme achieves a stabler identification rate and lower computational complexity than the schemes based on the Mel-frequency cepstral coefficients. ? The Institution of Engineering and Technology 2014.