Hybrid Model Design for Baseline-Context-Independent-Mono-Phone Automatic Speech Recognition

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2015 by IJETT Journal
Volume-27 Number-6
Year of Publication : 2015
Authors : Amr M. Gody, Rania Ahmed AbulSeoud, Marian M.Ibraheem
  10.14445/22315381/IJETT-V27P255

MLA 

Amr M. Gody, Rania Ahmed AbulSeoud, Marian M.Ibraheem"Hybrid Model Design for Baseline-Context-Independent-Mono-Phone Automatic Speech Recognition", International Journal of Engineering Trends and Technology (IJETT), V27(6),304-313 September 2015. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group

Abstract
In this research new hybrid model for Automatic Speech Recognition is introduced. The model is constructed as a hybrid of Mel-Scale and 15-Bit Best Tree Encoding (BTE). Best Tree Encoding is first introduced in [1] as new feature for solving Automatic Speech recognition (ASR). The model is compared with MFCC. HTK is used as Recognition Engine. The model is also compared with the old generations of BTE to evaluate the performance of Context-independent mono-phone recognition of English language. Sub class of TIMIT database is used in all experiments through this research .The proposed model gives success rate equals to 96%with respect to the success rate of the reference MFCC in solving the same problem but vector size is 33% of MFCC vector size.

 References

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Keywords
Automatic Speech recognition, English Phone Recognition, Wavelet packets, Mel scale, MFCC, HTK and Best Tree Encoding.