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Idioma: inglés
Editorial: LAP LAMBERT Academic Publishing, 2013
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Speech Recognition System using MATLAB | Design, Implementation, and Samples Codes | Ahmad A. M. Abushariah (u. a.) | Taschenbuch | 112 S. | Englisch | 2013 | LAP LAMBERT Academic Publishing | EAN 9783846503768 | Verantwortliche Person für die EU: OmniScriptum GmbH & Co. KG, Bahnhofstr. 28, 66111 Saarbrücken, info[at]akademikerverlag[dot]de | Anbieter: preigu.
N° de ref. del artículo 106795399
- Título
- Speech Recognition System using MATLAB | Design, Implementation, and Samples Codes
- Autor
- Ahmad A. M. Abushariah (u. a.)
- Editorial
- LAP LAMBERT Academic Publishing
- Año de publicación
- 2013
- Estado
- Neu
- Encuadernación
- Taschenbuch
- Idioma
- inglés
- ISBN 10
- 3846503762
- ISBN 13
- 9783846503768
- Peso del artículo
- 185 gramos
- Dimensiones
- 220 x 150 x 8 mm
- Catálogos de vendedores
- Bücher
Research in automatic speech recognition has been done for almost four decades. This project aims to develop automated English digits speech recognition system using Matlab. The system is able to recognize the spoken utterances by translating the speech waveform into a set of feature vectors using Mel Frequency Cepstral Coefficients (MFCC) technique, which then estimates the observation likelihood by using the Forward algorithm. The Hidden Markov Model (HMM) parameters are estimated by applying the Baum-Welch algorithm on previously trained samples. The most likely sequence is then decoded using Viterbi algorithm, thus producing the recognized word. This project focuses on all English digits from (Zero through Nine), which is based on isolated words structure. Two modules were developed, namely the isolated words speech recognition and the continuous speech recognition. Both modules were tested in both clean and noisy environments and showed relatively sucessful recognition rates. The samples of Matlab codes were provided in the Appendix.
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Reseña del editor
Research in automatic speech recognition has been done for almost four decades. This project aims to develop automated English digits speech recognition system using Matlab. The system is able to recognize the spoken utterances by translating the speech waveform into a set of feature vectors using Mel Frequency Cepstral Coefficients (MFCC) technique, which then estimates the observation likelihood by using the Forward algorithm. The Hidden Markov Model (HMM) parameters are estimated by applying the Baum-Welch algorithm on previously trained samples. The most likely sequence is then decoded using Viterbi algorithm, thus producing the recognized word. This project focuses on all English digits from (Zero through Nine), which is based on isolated words structure. Two modules were developed, namely the isolated words speech recognition and the continuous speech recognition. Both modules were tested in both clean and noisy environments and showed relatively sucessful recognition rates. The samples of Matlab codes were provided in the Appendix.
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