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Implementation and Performance Analysis of PSTTD system: Punjabi Speech to Text Detection(PSTTD) system under different scenarios - Couverture souple

Kadyan, Virender; Chopra, Ashish

 
9783659939877: Implementation and Performance Analysis of PSTTD system: Punjabi Speech to Text Detection(PSTTD) system under different scenarios
Couverture souple
ISBN 10 : 3659939870 ISBN 13 : 9783659939877
Editeur : LAP LAMBERT Academic Publishing, 2017

Synopsis

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.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

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.

Biographie de l'auteur

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.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2017
Langue
anglais
ISBN 10 
3659939870
ISBN 13 
9783659939877
Reliure
Broché
Nombre de pages
112
Coordonnées du fabricant
non disponible
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