Automatic Segmentation of Speech at the Phonetic Level
Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
A Speech/Music Discriminator of Radio Recordings Based on Dynamic Programming and Bayesian Networks
IEEE Transactions on Multimedia
Improvements on automatic speech segmentation at the phonetic level
CIARP'11 Proceedings of the 16th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
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In this paper, we present an automatic speech segmentation system based on acoustical clustering plus dynamic time warping. Our system operates at three stages, the first one obtains a coarse segmentation as a starting point to the second one. The second stage fixes phoneme boundaries in an iterative process of progressive refinement. The third stage makes a finer adjustment by considering some acoustic parameters estimated at a higher subsampling rate around the boundary to be adjusted. No manually segmented utterances are used in any stage. The results presented here demonstrate a good learning capability of the system, which only uses the phonetic transcription of each utterance. Our approach obtains similar results than the ones reported by previous related works on TIMIT database.