Abstract
Speech recognition has been developed from theoretical methods practical systems. Since 90’s people have moved their interests to the difficult task of Large Vocabulary Continuous Speech Recognition (LVCSR) and indeed achieved a great progress. Meanwhile, many well-known research and commercial institutes have established their recognition systems including via Voice system IBM, Whisper system by Microsoft etc. In this paper we have developed a simple and efficient algorithm for the recognition of speech signal for speaker independent isolated word recognition system. We use Mel frequency cepstral coefficients (MFCCs) as features of the recorded speech. A decoding algorithm is proposed for recognizing the target speech computing the cepstral distance of the cepstral coefficients. Simulation experiments were carried using MATLAB here the method produced relatively good (85% word recognition accuracy) results.
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Pramanik, A., Raha, R. (2013). Speaker Independent Word Recognition Using Cepstral Distance Measurement. In: Abraham, A., Thampi, S. (eds) Intelligent Informatics. Advances in Intelligent Systems and Computing, vol 182. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32063-7_25
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DOI: https://doi.org/10.1007/978-3-642-32063-7_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32062-0
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