An Alternative Voice Communication Aid based on ASR
Keywords:
MFCC, ASR, DTW, Voice Communication AidAbstract
This paper include the implementation aspects of alternative communication aid for the person suffering from speech impairment problem. The Alternative Communication Aid (AVCA) is an automatic voice recognition system that uses the concept of automatic speech recognition system (ASR) and announce the constructed sentence. For feature extraction from sound waves we have used mel frequency cepstral coefficient (MFCC) and DTW algorithm to find the distance between two vectors. This system also incorporate the feature of record voice samples in runtime.
References
- Zhanyu Ma, Hong Yu, Zheng-Hua Tan And Jun Guo, "Text-Independent Speaker Identification Using the Histogram Transform Model", IEEE Access, VOLUME 4, 2016, pp(9733-9739)
- SadaokiFurui, 50 years of Progress in speech and Speaker Recognition Research , ECTI Transactions on Computer and Information Technology,Vol.1. No.2 November 2005.
- K.H.Davis, R.Biddulph, and S.Balashek, Automatic recognition of spoken Digits, J.Acoust.Soc.Am., 24(6):637-642,1952.
- H.F.Olson and H.Belar, Phonetic Typewriter , J.Acoust.Soc.Am.,28(6):1072-1081,1956.
- D.B.Fry, Theoritical Aspects of Mechanical speech Recognition , and P.Denes, The design and Operation of the Mechanical Speech Recognizer at Universtiy College London, J.British Inst. Radio Engr., 19:4,211-299,1959.
- J.W.Forgie and C.D.Forgie, Results obtained from a vowel recognition computer program , J.A.S.A., 31(11),pp.1480-1489.1959.
- J.Suzuki and K.Nakata, Recognition of Japanese Vowels Preliminary to the Recognition of Speech , J.Radio Res.Lab37(8):193-212,1961.
- T.Sakai and S.Doshita, The phonetic typewriter, Information processing 1962 , Proc.IFIP Congress, 1962.
- K.Nagata, Y.Kato, and S.Chiba, Spoken Digit Recognizer for Japanese Language , NEC Res.Develop., No.6,1963.
- T.B.Martin, A.L.Nelson, and H.J.Zadell, Speech Recognition b Feature Abstraction Techniques , Tech.Report AL-TDR-64-176,Air Force Avionics Lab,1964.
- T.K.Vintsyuk, Speech Discrimination by Dynamic Programming , Kibernetika, 4(2):81-88,Jan.-Feb.1968.
- C.C.Tappert,N.R.Dixon, A.S.Rabinowitz, andW.D.Chapman, Automatic Recognition of Continuous Speech Utilizing Dynamic Segmentation, DualClassification, Sequential Decoding and Error Recover , Rome Air Dev.Cen, Rome, NY,Tech.Report TR-71-146,1971.
- F.Jelinek, L.R.Bahl, and R.L.Mercer, Design of a Lingusistic Statistical Decoder for the Recognition ofContinuous Speech , IEEE Trans.InformationTheory,IT- 21:250-256,1975.
- F.Jelinek, The Development of an ExperimentalDiscrete Dictation Recognizer , Proc.IEEE,73(11):1616- 624,1985.
- GEMMA HORNERO, DAVID CONDE, MARCOS QUÍLEZ, SERGIO DOMINGO, MARÍA PEÑA RODRÍGUEZ, BORJA ROMERO, AND OSCAR CASAS, "A Wireless Augmentative and Alternative Communication System for People With Speech Disabilities", IEEE Access, VOLUME 3, 2015, PP 1288-1297
- Deepak Joshi, Shiv Dutt Joshi, “Improved Language Identification Using Sampling Rate Compensation & Gender Based Language Models For Indian Languages”, 978-1-4673-6190-3/13/$31.00 ©2013 IEEE
- Mark S. Hawley, Stuart P. Cunningham, Phil D. Green, Pam Enderby, Rebecca Palmer, Siddharth Sehgal, and Peter O’Neill, “A Voice-Input Voice-Output Communication Aid for People With Severe Speech Impairment”, IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, VOL. 21, NO. 1, JANUARY 2013, Pg 23-31
Downloads
Published
Issue
Section
License
Copyright (c) IJSRSET

This work is licensed under a Creative Commons Attribution 4.0 International License.