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A Comparative Study of Feature Extraction Methods Applied to Continuous Speech Recognition in Romanian Language

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2 Author(s)
Corneliu Octavian Dumitru ; Politehnica University Bucharest, Faculty of Electronics Telecommunication and Information Technology, Splaiul Independentei 313, Bucharest, Romania. E-mail: ; Inge Gavat

This paper describes continuous speech recognition experiments on a Romanian language speech database, by using hidden Markov models (EMM). We compare the recognition rates obtained in our ASR system realising front-ends based on features extracted by perceptual variants of cepstral analysis and linear prediction and by simple linear prediction. The best results obtained with 36 coefficients mel-frequency cepstral coefficients (MFCC) are used as basis to rank the front-ends based on LPC. The second rank is very promising for the performance obtained with 5 perceptual linear prediction (PLP) coefficients, obviously better at the last ranked performance of the simple linear prediction coefficients (LPC). We reorganized the database as follows: one database for male speakers, one database for female speakers and one database for both male and female speakers

Published in:

Proceedings ELMAR 2006

Date of Conference:

June 2006