A Statistical Model for Word Discovery in Transcribed Speech

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A statistical model for segmentation and word discovery in continuous speech is presented. An incremental unsupervised learning algorithm to infer word boundaries based on this model is described. Results of empirical tests showing that the algorithm is competitive with other models that have been used for similar tasks are also presented.
Expanded version of ICML-01 paper (pp.569--576)

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Computation and Language, I.2.6;I.2.7

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http://salesiana.dossiersoluciones.com/handle/123456789/30937

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/cs/0111065
 http://arxiv.org/abs/cs/0111065
 Computational Linguistics, 27(3), pp.352--372, 2001

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arXiv