HMM-Based speech recognition using adaptive framing

Goh, Y.H. and Paramesran, Raveendran (2009) HMM-Based speech recognition using adaptive framing. In: IEEE Region 10 Conference 2009, NOV 23-26, 2009 , Singapore.

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A common approach in mapping a signal to discrete events is to define a set of symbols that correspond to useful acoustic features of the signal over a short constant time interval. This paper proposes a Hidden Markov Models (HMM) based speech recognition by using cepstrum feature of the signal over adaptive time interval. First pitch period is detected by dyadic wavelet transform and divides the voiced speech signal according to the detected period. Then, system performs HMM-based speech recognition using cepstrum feature to classify the speech signals. Two speech recognition systems have been developed, one is based on constant time framing and the other is adaptive framing. The results are compared and found that adaptive framing method shows better result in both data distribution and recognition rate.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Univ Malaya, Dept Elect Engn, Kuala Lumpur 50603, Malaysia
Uncontrolled Keywords: Speech Recognition; HMM-based; Adaptive Time Intervals
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Engineering
Depositing User: Mr. Faizal Hamzah
Date Deposited: 18 Oct 2011 07:48
Last Modified: 20 Sep 2019 08:31

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