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Published in:
2017 | OriginalPaper | Chapter
Hindi Dialect (Bangro) Spoken Language Recognition (HD-SLR) System Using Sphinx3
Authors : Virender Kadyan, Amitoj Singh, Parth Wadhwa
Published in: Proceeding of International Conference on Intelligent Communication, Control and Devices
Publisher: Springer Singapore
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Abstract
A Hindi dialect (Bangro) Spoken Language Recognition (HD-SLR) System is designed to recognize language from a given spoken utterance. Paper focuses on the influence of Hindi dialects, i.e., Haryanvi spoken by males and females of different age groups ranging from 18 to 40 years. The system is trained and tested with the help of Sphinx3 toolkit on Linux platform. Also, it has been tried with semicontinuous speech corpus in clean environment of around 5 h that includes 1000 distinct Hindi dialect words spoken in different parts of Haryana. The dialectal information of the input speech signals is extracted with the help of MFCC technique and the same system is then tested on the basis of utterance level. The Speaker Independent Semicontinuous (SISC) word recognition system has an average of 75–85 % accuracy rate by native and nonnative speakers of Hindi dialect.