Detection of abrupt spectral changes using support vector machines an application to audio signal segmentation

@article{Davy2002DetectionOA,
  title={Detection of abrupt spectral changes using support vector machines an application to audio signal segmentation},
  author={Manuel Davy and Simon J. Godsill},
  journal={2002 IEEE International Conference on Acoustics, Speech, and Signal Processing},
  year={2002},
  volume={2},
  pages={II-1313-II-1316}
}
In this paper, we introduce an hybrid time-frequency/support vector machine algorithm for the detection of abrupt spectral changes. A stationarity index is derived from support vector novelty detection theory by using sub-images extracted from the time-frequency plane as feature vectors. Simulations show the efficiency of this new algorithm for audio signal segmentation, compared to another nonparametric detector. 
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