A process to improve the accuracy of voice recognition system by using word correction system

Authors

  • Islam N Computer Science and Engineering Department, Ganga Institute of Technology & Management, India
  • Ranga KK Computer Science and Engineering Department, Ganga Institute of Technology & Management, India

Keywords:

Algorithm, Speech, windows speech recognition devices

Abstract

Recently, computer speech recognition is used to solve problems and any plan based task, predictable features of the user's behaviour may be inferred and used to aid the recognition of the speech input. The MINDS system generates expectations of what will be said next and uses them to assist speech recognition. Since a user does not always conform to system expectations, MINDS handles violated expectations. We use a common knowledge to enable the speech system to give priority to recognizing what a user is most likely to say. Each time the words spoken by speaker will display in the computer which is generated by the speech recognizer. In it words correction system has been implemented. With the help of words correction system, speaker can correct the word manually through keyboard, if the word produced by the voice recogniser is not similar as the speaker dictates to the computer. The word correction system is used to correct misrecognised words. This system will bring cent percent accuracy in voice recognition system.

References

K. Lee, Automatic, Speech Recognition: the development to f the Sphinx System, Kluwer Academic Publishers, Norwell, Mass. 1989

L. R. Bahl et al., “Speech Recognition of a Natural Text Read as Isolated Words,” Proc. IEEE IntI Conf. Acoustics, Speech, and Signal Processing, April 1981, pp. 1,168-1,17 1.

D.O. Kimbal et al., “Recognition Performance and Grammatical Constraints,” Proc. DARPA Speech Recognition Workshop, Feb. 1986, pp. 53-59.

D. O‟Shaughnessy, Speech Communication: Human and Machine, Addison- Wesley, Reading, Mass., 1987.

M.A. Franzini, M.J. Witbrock, and K.-F. Lee, “SpeakerIndependent Recognition of Connected Utterances Using Recurrent and Non recurrent Neural Networks,” Proc. Int‟l Joint Conf. Neural Networks, V01.2, Washington, DC, June 1989, pp.11-1 to II-

J. Mariani, “Recent Advances in Speech Processing,”Proc. IEEE Intl Conf. Acoustics, Speech, and Signal Processing, Glasgow, Scotland. May 1989, pp. 429- 440.

M.-W. Fung et al., “Improved Speaker Adaptation Using Text-Dependent Spectral Mappings,” Proc. IEEE Int‟lConf. Acoustics, Speech. and Signal Processing, New York City, 1988, pp. 131-134.

D.B. Paul, “The Lincoln Robust Continuous Speech Recognizer,” Proc. IEEE Int‟l Conf. Acoustics, Speech, and Signal Processing, Glasgow, Scotland, 1989, pp. 449-452.

H. Murveit and M. Weintraub, “1,000- Word SpeakerIndependent Continuous- Speech Recognition Using Hidden Markov Models,” Proc. IEEE Int‟l Conf, Acoustics, Speech, and Signal Processing, New York City, 1988, pp. 115-1 18.

W. Wylegala, “A 20,000-Word Recognizer Based on Statistical Evaluation Methods,” Speech Technology Msagazine, Apr./May 1989, pp, 16-18.

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Published

2024-02-26

How to Cite

Islam, N., & Ranga, K. K. (2024). A process to improve the accuracy of voice recognition system by using word correction system. COMPUSOFT: An International Journal of Advanced Computer Technology, 3(06), 822–824. Retrieved from https://ijact.in/index.php/j/article/view/146

Issue

Section

Original Research Article

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