Speech Recognition System using MATLAB: Design, Implementation, and Samples Codes

 
9783846503768: Speech Recognition System using MATLAB: Design, Implementation, and Samples Codes
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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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About the Author:

::: Ahmad Abushariah graduated from International Islamic University Malaysia in 2009, and is currently pursuing Master degree at IIUM. His research interest is speech and image processing. ::: Teddy Surya Gunawan received his PhD degree from UNSW in 2007 specializing in signal processing. He is currently an Assistant Professor at IIUM.

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Book Description Condition: New. Publisher/Verlag: LAP Lambert Academic Publishing | Design, Implementation, and Samples Codes | 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. | Format: Paperback | Language/Sprache: english | 165 gr | 220x150x6 mm | 112 pp. Seller Inventory # K9783846503768

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Book Description LAP Lambert Academic Publishing Mai 2013, 2013. Taschenbuch. Condition: Neu. Neuware - 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. 112 pp. Englisch. Seller Inventory # 9783846503768

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Book Description LAP Lambert Academic Publishing Mai 2013, 2013. Taschenbuch. Condition: Neu. Neuware - 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. 112 pp. Englisch. Seller Inventory # 9783846503768

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Book Description LAP Lambert Academic Publishing, Germany, 2013. Paperback. Condition: New. Language: English . Brand New Book. 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. Seller Inventory # KNV9783846503768

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