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This correspondence describes a method of automated segmentation of speech assuming the signal is
continuously time varying rather than the traditional short time stationary model. It has been shown that this representation gives comparable if not marginally better results than the other techniques for automated segmentation. A formulation of the ‘Bach’ (music semitonal) frequency scale filter-bank is proposed. A comparative study has been made of the performances using Mel, Bark and Bach scale filter banks considering this model. The preliminary results show up to 80 % matches within 20 ms of the manually segmented data, without any information of the content of the text and without any language dependence. ‘Bach’ filters are seen to marginally outperform the other filters.

Added on August 5, 2014


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  • Product Type : Research Paper
  • License Type : Freeware
  • System Requirement : Not Applicable
  • Author : G. Ananthakrishnan, H. G. Ranjani, A.G. Ramakrishnan
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