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Implementation and Performance Analysis of PSTTD system: Punjabi Speech to Text Detection(PSTTD) system under different scenarios - Brossura
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In modern speech recognition systems, there are a set of Feature Extraction Techniques (FET) like Mel-frequency cepstral coefficients (MFCC) or perceptual linear prediction coefficients (PLP) are mainly used. As compared to the conventional FET like LPCC etc, these approaches are provide a better speech signal that contains the relevant information of the speech signal uttered by the speaker during training and testing of the Speech To Text Detection System (STTDS) for different Indian languages. In this dissertation, variation in the parameters values of FET’s like MFCC, PLP are varied at the front end along with dynamic HMM topology at the back end and then the speech signals produce by these techniques are analyzed using HTK toolkit. The cornerstone of all the current state-of-the-art STTDS is the use of HMM acoustic models. In our work the effectiveness of proposed FET(MFCC, PLP features) are tested and the comparison is done among the FET like MFCC and PLP acoustic features to extract the relevant information about what is being spoken from the audio signal and experimental results are computed with varying HMM topology at the back end.
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L'autore
Er. Virender Kadyan currently working as an Assistant Professor at Chitkara University, Punjab. He has done his M.Tech. degree from Department of Computer Science & Engineering at DVIET, INDIA. His research interests include automatic speech recognition.Dr. Ashish Chopra currently working as an Assistant Professor at NIT, Kurukshetra, India.
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Implementation and Performance Analysis of PSTTD system
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LAP LAMBERT Academic Publishing Jan 2017, 2017
ISBN 10: 3659939870
ISBN 13: 9783659939877
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In modern speech recognition systems, there are a set of Feature Extraction Techniques (FET) like Mel-frequency cepstral coefficients (MFCC) or perceptual linear prediction coefficients (PLP) are mainly used. As compared to the conventional FET like LPCC etc, these approaches are provide a better speech signal that contains the relevant information of the speech signal uttered by the speaker during training and testing of the Speech To Text Detection System (STTDS) for different Indian languages. In this dissertation, variation in the parameters values of FET's like MFCC, PLP are varied at the front end along with dynamic HMM topology at the back end and then the speech signals produce by these techniques are analyzed using HTK toolkit. The cornerstone of all the current state-of-the-art STTDS is the use of HMM acoustic models. In our work the effectiveness of proposed FET(MFCC, PLP features) are tested and the comparison is done among the FET like MFCC and PLP acoustic features to extract the relevant information about what is being spoken from the audio signal and experimental results are computed with varying HMM topology at the back end. 112 pp. Englisch. Codice articolo 9783659939877
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Implementation and Performance Analysis of PSTTD system: Punjabi Speech to Text Detection(PSTTD) system under different scenarios
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LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3659939870
ISBN 13: 9783659939877
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Implementation and Performance Analysis of PSTTD system : Punjabi Speech to Text Detection(PSTTD) system under different scenarios
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LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3659939870
ISBN 13: 9783659939877
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In modern speech recognition systems, there are a set of Feature Extraction Techniques (FET) like Mel-frequency cepstral coefficients (MFCC) or perceptual linear prediction coefficients (PLP) are mainly used. As compared to the conventional FET like LPCC etc, these approaches are provide a better speech signal that contains the relevant information of the speech signal uttered by the speaker during training and testing of the Speech To Text Detection System (STTDS) for different Indian languages. In this dissertation, variation in the parameters values of FET's like MFCC, PLP are varied at the front end along with dynamic HMM topology at the back end and then the speech signals produce by these techniques are analyzed using HTK toolkit. The cornerstone of all the current state-of-the-art STTDS is the use of HMM acoustic models. In our work the effectiveness of proposed FET(MFCC, PLP features) are tested and the comparison is done among the FET like MFCC and PLP acoustic features to extract the relevant information about what is being spoken from the audio signal and experimental results are computed with varying HMM topology at the back end. Codice articolo 9783659939877
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Implementation and Performance Analysis of PSTTD system: Punjabi Speech to Text Detection(PSTTD) system under different scenarios
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LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3659939870
ISBN 13: 9783659939877
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Kadyan VirenderEr. Virender Kadyan currently working as an Assistant Professor at Chitkara University, Punjab. He has done his M.Tech. degree from Department of Computer Science & Engineering at DVIET, INDIA. His research interests i. Codice articolo 158877981
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Implementation and Performance Analysis of PSTTD system: Punjabi Speech to Text Detection(PSTTD) system under different scenarios
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ISBN 10: 3659939870
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Implementation and Performance Analysis of PSTTD system: Punjabi Speech to Text Detection(PSTTD) system under different scenarios
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LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3659939870
ISBN 13: 9783659939877
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Implementation and Performance Analysis of PSTTD system
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ISBN 13: 9783659939877
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In modern speech recognition systems, there are a set of Feature Extraction Techniques (FET) like Mel-frequency cepstral coefficients (MFCC) or perceptual linear prediction coefficients (PLP) are mainly used. As compared to the conventional FET like LPCC etc, these approaches are provide a better speech signal that contains the relevant information of the speech signal uttered by the speaker during training and testing of the Speech To Text Detection System (STTDS) for different Indian languages. In this dissertation, variation in the parameters values of FET's like MFCC, PLP are varied at the front end along with dynamic HMM topology at the back end and then the speech signals produce by these techniques are analyzed using HTK toolkit. The cornerstone of all the current state-of-the-art STTDS is the use of HMM acoustic models. In our work the effectiveness of proposed FET(MFCC, PLP features) are tested and the comparison is done among the FET like MFCC and PLP acoustic features to extract the relevant information about what is being spoken from the audio signal and experimental results are computed with varying HMM topology at the back end.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 112 pp. Englisch. Codice articolo 9783659939877
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