Abstract
In this paper a description of an algorithm purposed to a speech recognition problem is presented. Samples were obtained from people in different ages, from 8 to 70 years. Authors’ attention was concentrated on finding an efficient voice descriptor for the speech recognition process. To reach this goal Toeplitz matrices were used. The recognition process is based on k Nearest Neighbors algorithm and the analysis is carried out only for voiced parts of speech. Different distance metrics were compared in the aim of kNN optimization. In the research the influence of the sex recognition on final results is confirmed. The algorithm was tested for signals sampled with the rate of 8 kHz to keep all the necessary information contained in human voice.
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Karwan, J., Saeed, K. (2011). A New Algorithm for Speech and Gender Recognition on the Basis of Voiced Parts of Speech. In: Chaki, N., Cortesi, A. (eds) Computer Information Systems – Analysis and Technologies. Communications in Computer and Information Science, vol 245. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27245-5_15
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DOI: https://doi.org/10.1007/978-3-642-27245-5_15
Publisher Name: Springer, Berlin, Heidelberg
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