Isolated word recognition on an embedded system

Authors:
Mahmut Meral;Muhittin Gökmen
Affiliations:
Computer Engineering Department, istanbul Technical University, istanbul, Turkiye;Computer Engineering Department, istanbul Technical University, istanbul, Turkiye
Venue:
MUSP'06 Proceedings of the 6th WSEAS international conference on Multimedia systems & signal processing
Year:
2006

Citing 3
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Fundamentals of speech recognition

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Discrete Time Processing of Speech Signals

Discrete Time Processing of Speech Signals
Pervasive Speech Recognition

IEEE Pervasive Computing

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Abstract

In this paper, an embedded isolated word recognition system, which is designed for command and control applications, is presented. The hardware is designed by using a 32 bit general purpose ARM7TDMI cored microcontroller and required peripherals. Vector Quantization (VQ) and Discrete Hidden Markov Model (HMM) based speech recognition algorithms are implemented on the embedded system. The system is tested on a data set containing fifty four Turkish words taken from forty speakers. Using this data set, the VQ classifier obtained 99% and HMM classifier obtained about 97% average recognition rates in simulations.