Abstract
In speech recognition, the training (or learning) process plays an important role. When a good training model for a speech pattern is obtained, this not only enhances the speed of recognition tremendously, but also improves the quality of the overall performance in recognizing the speech utterance. In general, there are two classic approaches for this development, namely, Dynamic Time Warping (DTW) and the Hidden Markov Model (HMM).
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© 1999 Springer-Verlag London
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Man, K.F., Tang, K.S., Kwong, S. (1999). Genetic Algorithms in Speech Recognition Systems. In: Genetic Algorithms. Advanced Textbooks in Control and Signal Processing. Springer, London. https://doi.org/10.1007/978-1-4471-0577-0_8
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DOI: https://doi.org/10.1007/978-1-4471-0577-0_8
Publisher Name: Springer, London
Print ISBN: 978-1-85233-072-9
Online ISBN: 978-1-4471-0577-0
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