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Implementation of Automatic Speech Recognition for Low-Power Miniaturized Devices
Auteur(s)
Grassi, Sara
Ansorge, Michael
Pellandini, Fausto
Farine, Pierre-André
Date de parution
2003-10-03
In
Proceedings of the 5th COST 276 Workshop on Information and Knowledge Management for Integrated Media Communication, COST (European Cooperation in the field of Scientific and Technical Research), 2003/276/5/59-64
Résumé
This paper describes the development and implementation of a discrete speech recognizer for application in miniaturized, portable low-power devices. The recognizer is based on Hidden Markov Models (HMMs) and uses Linear Predictive Coefficients (LPC) converted to cepstrum to parameterize the input speech. The implemented recognizer has a complexity of 0.67 MIPS and a recognition performance of 97.69 % when recognizing isolated digits in French. The physical implementation of the recognizer was done on a proprietary ASIC DSP and verified using fast prototyping on FPGA.
Identifiants
Type de publication
journal article
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