Abstract
This paper presents an approach to the recognition of speech signal using frequency spectral information with Mel frequency for the improvement of speech feature representation in a HMM based recognition approach. A frequency spectral information is incorporated to the conventional Mel spectrum base speech recognition approach. The Mel frequency approach exploits the frequency observation for speech signal in a given resolution which results in resolution feature overlapping resulting in recognition limit. Resolution decomposition with separating frequency is mapping approach for a HMM based speech recognition system. The Simulation results show a improvement in the quality metrics of speech recognition with respect to computational time, learning accuracy for a speech recognition system.
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Patel, I., Srinivas Rao, Y. (2010). A Frequency Spectral Feature Modeling for Hidden Markov Model Based Automated Speech Recognition. In: Meghanathan, N., Boumerdassi, S., Chaki, N., Nagamalai, D. (eds) Recent Trends in Networks and Communications. WeST VLSI NeCoM ASUC WiMoN 2010 2010 2010 2010 2010. Communications in Computer and Information Science, vol 90. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14493-6_15
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DOI: https://doi.org/10.1007/978-3-642-14493-6_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14492-9
Online ISBN: 978-3-642-14493-6
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