Abstract
Hidden Markov Models are widely used for recognition of any patterns appearing in an input signal. In the work HMM’s were used to recognize two kind of speech disorders in an acoustic signal: prolongation of fricative phonemes and blockades with repetition of stop phonemes.
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Wiśniewski, M., Kuniszyk-Jóźkowiak, W., Smołka, E., Suszyński, W. (2007). Automatic Detection of Disorders in a Continuous Speech with the Hidden Markov Models Approach. In: Kurzynski, M., Puchala, E., Wozniak, M., Zolnierek, A. (eds) Computer Recognition Systems 2. Advances in Soft Computing, vol 45. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75175-5_56
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DOI: https://doi.org/10.1007/978-3-540-75175-5_56
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-75174-8
Online ISBN: 978-3-540-75175-5
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