Attacking the problem of continuous speech segmentation into basic units

Abstract

The paper considers the algorithm of continuous speech segmentation into basic units, namely phonemes, certain combination of phonemes and pauses. The algorithm is based on speech signal transformation into a two-dimensional image, i.e. an autocorrelation portrait. To determine the boundaries of speech units the portraits of the analyzed signal are aligned with the model portraits of each speech unit. The authors apply the dynamic programming to find out the optimal distance between portraits.

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Cite this paper

@inproceedings{Andreev2017AttackingTP, title={Attacking the problem of continuous speech segmentation into basic units}, author={Ivan A Andreev}, year={2017} }