The Comprehensive Analysis Speech Recognition System

Dr. Anubhav Soni; Dr. Jitendra

doi:10.55524/ijircst.2021.9.6.27

Abstract

Automated computer speech detection has been a goal of research for almost four decades. The idea underlying the development of a voice recognition system is that it is beneficial for people to communicate with a computer, robot or another device via speech. Researchers want to utilize people's voices in an integrated environment to provide customers comfort and flexibility in today's era. Speech recognition is dependent on the input voice signal. It enables the computer to transform the voice signal to text or instructions using the technique of recognition and understanding. This article describes the fundamental concept of speaking recognition, types of voice recognition, difficulties with speech recognition, several ways to gather characteristics, and different pattern-matching algorithms to identify the different speakers. The technology of voice recognition is inspired by a wide vocabulary automated speech recognition system which allows language-independent operation and continuous speaking in a foreign language.

Keywords

ANN, Feature Extraction, Markov Model, Speech Recognition, Voice Recognition.

References

[1]Naziya S. S, Deshmukh RR. Speech Recognition System – A Review. IOSR J Comput Eng. 2016;

[2]Këpuska V. Comparing Speech Recognition Systems (Microsoft API, Google API And CMU Sphinx). Int J Eng Res Appl. 2017;

[3]Continuous Speech Recognition System A Review. Asian J Comput Sci Inf Technol. 2014;

[4]Washani N, Sharma S. Speech Recognition System: A Review. Int J Comput Appl. 2015;

[5]K.Saksamudre S, Shrishrimal PP, Deshmukh RR. A Review on Different Approaches for Speech Recognition System. Int J Comput Appl. 2015;

[6]Swamy S, K.V R. An Efficient Speech Recognition System. Comput Sci Eng An Int J. 2013;

[7]Rami M, Svitlana M, Lyashenko V, Belova N. Speech Recognition Systemsâ€¯: A Comparative Review. IOSR J Comput Eng. 2017;

[8]Xiong W, Wu L, Alleva F, Droppo J, Huang X, Stolcke A. The Microsoft 2017 Conversational Speech Recognition System. In: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. 2018.

[9]Markovnikov NM, Kipyatkova IS. An analytic survey of end-to-end speech recognition systems. SPIIRAS Proc. 2018;

[10]Kurzekar PK, Deshmukh RR, Waghmare VB, Shrishrimal PP. A Comparative Study of Feature Extraction Techniques for Speech Recognition System. Int J Innov Res Sci Eng Technol. 2014;

Cites this article as

D. A. Soni, D. Jitendra, "The Comprehensive Analysis Speech Recognition System", International Journal of Innovative Research in Engineering & Management (IJIREM), Vol-9, Issue-6, Page No-118-122, 2021. Available from: https://doi.org/10.55524/ijircst.2021.9.6.27

Corresponding Author

Dr. Anubhav Soni

SOMC, Sanskriti University, Mathura, Uttar Pradesh, India (anubhavs.somc@sanskriti.edu.in)

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