Soft Computing Implementation of Automatic Speech Recognition : Isolated words recognition

Himanshu Chaurasiya

ISBN 10: 3843365709 / ISBN 13: 9783843365703

Editore: LAP LAMBERT Academic Publishing, 2010

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nach der Bestellung gedruckt Neuware - Printed after ordering - This work assimilates an introduction to the Human speech production system, Fundamentals of speech recognition, the methods for data analysis as well as the theoretical background of past research, Soft computing, implementation as a form of Methodology, Results and Conclusion & future work . Soft Computing includes a family consisting of many members, namely Genetic Algorithms (GAs), Neural Networks and others.With this text, you will find a balance between theory and implementation that allows you to build your understanding of the basic concepts, Methodology and a results obtained using various neural networks with Recognition percentages of isolated words in two different languages and Confusion Matrix for radial basis similarly for probabilistic. This work also shows the Comparative analysis of results from the Recognition using GA and without GA. The use of GAs for feature optimizers is a novel concept in Automatic Speech Recognition hence the system becomes more robust to noise. Emphasis is laid more on a soft computing rather than on a hard one. Codice articolo 9783843365703

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Titolo: Soft Computing Implementation of Automatic ...

Casa editrice: LAP LAMBERT Academic Publishing

Data di pubblicazione: 2010

Legatura: Taschenbuch

Condizione: Neu

Descrizione articolo

Riassunto:

This work assimilates an introduction to the Human speech production system, Fundamentals of speech recognition, the methods for data analysis as well as the theoretical background of past research, Soft computing, implementation as a form of Methodology, Results and Conclusion & future work . Soft Computing includes a family consisting of many members, namely Genetic Algorithms (GAs), Neural Networks and others.With this text, you will find a balance between theory and implementation that allows you to build your understanding of the basic concepts, Methodology and a results obtained using various neural networks with Recognition percentages of isolated words in two different languages and Confusion Matrix for radial basis similarly for probabilistic. This work also shows the Comparative analysis of results from the Recognition using GA and without GA. The use of GAs for feature optimizers is a novel concept in Automatic Speech Recognition hence the system becomes more robust to noise. Emphasis is laid more on a soft computing rather than on a hard one.

L'autore:

Himanshu Chaurasiya is a Lecturer of Electronics and Comm. Engineering, presently at Amity University, Noida,U.P.,INDIA. He received B.Tech in 2006 and M.Tech in Digital Comm. Systems in 2008.He has been actively involved in teaching & research. His research interests include Automatic Speech Recognition, Soft Computing and Telecommunication.