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Please use this identifier to cite or link to this item: http://purl.org/purl/4190

Title: Speech Recognition of Malayalam Numbers
Authors: Kannan, Balakrishnan
Cini, Kurian
Keywords: Digit speech recognition
automatic data entry
PIN entry
Mel frequency cepstrum coefficient (MFCC)
Hidden Markov model (HMM)
Issue Date: 9-Dec-2009
Publisher: IEEE
Abstract: Digit speech recognition is important in many applications such as automatic data entry, PIN entry, voice dialing telephone, automated banking system, etc. This paper presents speaker independent speech recognition system for Malayalam digits. The system employs Mel frequency cepstrum coefficient (MFCC) as feature for signal processing and Hidden Markov model (HMM) for recognition. The system is trained with 21 male and female voices in the age group of 20 to 40 years and there was 98.5% word recognition accuracy (94.8% sentence recognition accuracy) on a test set of continuous digit recognition task.
Description: Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on
URI: http://dyuthi.cusat.ac.in/purl/4190
Appears in Collections:Dr. Kannan Balakrishnan

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