In this paper, we propose Mel-cepstrum modulation energy (MCME) as an extension of modulation energy (ME) for a feature to discriminate speech and music data. MCME is extracted from the time trajectory of Mel-frequency cepstral coefficients (MFCC), while ME is based on the spectrum. As cepstral coefficients are mutually uncorrelated, we expect MCME to perform better than ME. To find out the best modulation frequency for MCME, we make experiments with 4 Hz to 20 Hz modulation frequency, and we compare the results with those obtained from the ME and the MFCC based cepstral flux. In the experiments, 8 Hz MCME shows the best discrimination performance, and it yields a discrimination error reduction rate of 71% compared with 4 Hz ME. Compared with the cepstral flux (CF), it shows an error reduction rate of 53%. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Kim, B. W., Choi, D. L., & Lee, Y. J. (2007). Speech/music discrimination using mel-cepstrum modulation energy. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4629 LNAI, pp. 406–414). Springer Verlag. https://doi.org/10.1007/978-3-540-74628-7_53
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