Genre Classification and the Invariance of MFCC Features to Key and Tempo
暂无分享,去创建一个
[1] François Pachet,et al. Improving Timbre Similarity : How high’s the sky ? , 2004 .
[2] Thomas M. Cover,et al. Elements of Information Theory , 2005 .
[3] Daniel P. W. Ellis,et al. Song-Level Features and Support Vector Machines for Music Classification , 2005, ISMIR.
[4] Leon G. Higley,et al. Forensic Entomology: An Introduction , 2009 .
[5] Jan Larsen,et al. Improving music genre classification by short time feature integration , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..
[6] George Tzanetakis,et al. Musical genre classification of audio signals , 2002, IEEE Trans. Speech Audio Process..
[7] David Pearce,et al. The aurora experimental framework for the performance evaluation of speech recognition systems under noisy conditions , 2000, INTERSPEECH.
[8] Daniel P. W. Ellis,et al. Classifying Music Audio with Timbral and Chroma Features , 2007, ISMIR.
[9] Tao Li,et al. Factors in automatic musical genre classification of audio signals , 2003, 2003 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (IEEE Cat. No.03TH8684).
[10] Douglas Eck,et al. Aggregate features and ADABOOST for music classification , 2006, Machine Learning.
[11] Patrice Y. Simard,et al. Best practices for convolutional neural networks applied to visual document analysis , 2003, Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings..
[12] Lie Lu,et al. Content-based audio classification and segmentation by using support vector machines , 2003, Multimedia Systems.
[13] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[14] Werner Verhelst,et al. An overlap-add technique based on waveform similarity (WSOLA) for high quality time-scale modification of speech , 1993, 1993 IEEE International Conference on Acoustics, Speech, and Signal Processing.