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A Voice Signal Interpreter using Machine Learning Techniques

Rosy Mishra1 , Y. Sowjanya2 , Sushanta Meher3 , Mousumi Meher4

1 Dept. of CSE, Vikash Institute of Technology, Biju Patnaik University Of Technology,Baragrh,Odisha, India.
2 Dept. of CSE, Vikash Institute of Technology, Biju Patnaik University Of Technology,Baragrh,Odisha, India.
3 Dept. of CSE, Vikash Institute of Technology, Biju Patnaik University Of Technology,Baragrh,Odisha, India.
4 Dept. of CSE, Vikash Institute of Technology, Biju Patnaik University Of Technology,Baragrh,Odisha, India.

Section:Research Paper, Product Type: Journal
Vol.8 , Issue.2 , pp.22-27, Apr-2020

Online published on May 14, 2020


Copyright © Rosy Mishra, Y. Sowjanya, Sushanta Meher, Mousumi Meher . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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IEEE Style Citation: Rosy Mishra, Y. Sowjanya, Sushanta Meher, Mousumi Meher, “A Voice Signal Interpreter using Machine Learning Techniques,” International Journal of Scientific Research in Network Security and Communication, Vol.8, Issue.2, pp.22-27, 2020.

MLA Style Citation: Rosy Mishra, Y. Sowjanya, Sushanta Meher, Mousumi Meher "A Voice Signal Interpreter using Machine Learning Techniques." International Journal of Scientific Research in Network Security and Communication 8.2 (2020): 22-27.

APA Style Citation: Rosy Mishra, Y. Sowjanya, Sushanta Meher, Mousumi Meher, (2020). A Voice Signal Interpreter using Machine Learning Techniques. International Journal of Scientific Research in Network Security and Communication, 8(2), 22-27.

BibTex Style Citation:
@article{Mishra_2020,
author = {Rosy Mishra, Y. Sowjanya, Sushanta Meher, Mousumi Meher},
title = {A Voice Signal Interpreter using Machine Learning Techniques},
journal = {International Journal of Scientific Research in Network Security and Communication},
issue_date = {4 2020},
volume = {8},
Issue = {2},
month = {4},
year = {2020},
issn = {2347-2693},
pages = {22-27},
url = {https://www.isroset.org/journal/IJSRNSC/full_paper_view.php?paper_id=389},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.isroset.org/journal/IJSRNSC/full_paper_view.php?paper_id=389
TI - A Voice Signal Interpreter using Machine Learning Techniques
T2 - International Journal of Scientific Research in Network Security and Communication
AU - Rosy Mishra, Y. Sowjanya, Sushanta Meher, Mousumi Meher
PY - 2020
DA - 2020/05/14
PB - IJCSE, Indore, INDIA
SP - 22-27
IS - 2
VL - 8
SN - 2347-2693
ER -

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Abstract :
As we all know computer generated speech in immense now a days. In the current era of IT usage of computer generated speech is in great demand where as these speeches are still not human, and it`s not easy on the ears. The production quality system like Google Assistant, Apple Siri, Amazon Alexa, or Bixby as different from what a human generated speech would sound like. Many advances have been made in speech synthesis using neural network for easy accessing. Prime goal of this paper is to create an interpreter (Machine translator), to translate text to speech using a neural network. In this paper the main objective is to combine two techniques to produce a new product i.e. a new version of the translator. An artificial communicator is being developed to communicate with the universal language that is English for communication in between System & humans. These two technologies are used to link with each other & competence thoroughly. The purpose of this Application software is to permit different picture to convert its text in a language which is displayed in vocalizations. And it also permits for weakening vision in worst case seen in fields in picture format to understand language. A skill is being generated in machine through software for the Suitableness of humans for easy accessing.

Key-Words / Index Term :
Neural network, machine translator, Text to speech Translator, perceptron model

References :
[1] Wouter Gevaert, Georgi Tsenov, Valeri Mladenov, Senior Member, IEEE, “Neural Networks used for Speech Recognition” in the Journal of Automatic Control, University of Belgrade, vol. 20:1-7, 2010©.
[2] Malti Bansal, Shivam Sonkar “Text Image to Speech Conversion using Matlab and Microsoft SAPI” International Journal of Electronics, Electrical and Computational System IJEECS ISSN 2348-117X Volume 6, Issue 11 November 2017.
[3] Mohd Bilal Ganai1, Er Jyoti Arora2, “Implementation of Text to Speech Conversion Technique” in International Journal of Innovative Research in Computer and Communication Engineering Vol. 3, Issue 9, September 2015.
[4] Chaw Su Thu Thu1, Theingi Zin 2, “Implementation of Text to Speech Conversion” in International Journal of Engineering Research & Technology (IJERT) ISSN: 2278-0181Vol. 3 Issue 3, March – 2014.
[5]1N.Swetha,2K.Anuradha“Text-to-Speech Conversion” in International Journal of Advanced Trends in Computer Science and Engineering, Vol.2 , No.6, Pages : 269-278 (2013)Special Issue ( ICETEM) 2013 ISSN 2278-3091.
[6] Jisha Gopinath1, Aravind S2, Pooja Chandran3, “Text to Speech Conversion System using OCR” in International Journal of Emerging Technology and Advanced Engineering, ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 5, Issue 1, January 2015.
[7] Rubi Debnath, Vivek Hanumante, Disha Bhattacharjee, Deepti Tripathi, Sahadev Roy, “Multilingual Speech Translator using MATLAB” in International Conference on Electrical, Electronics, Signals, Communication and Optimization (EESCO) – 2015.
[8] Barik R.C., Mishra R. (2016) “Comparative Analogy on Classification and Clustering of Genomic Signal by a Novel Factor Analysis and F-Score Method”. In: Artificial Intelligence and Evolutionary Computations in Engineering Systems. Advances in Intelligent Systems and Computing, Vol 394. Springer, New Delhi.
[9] R. C. Barik, R. Pati and H. S. Behera,“ Robust signal processing compression for clustering of speech waveform and image spectrum”, IEEE International Conference on Communication and Signal Processing, April 2-4, 2015, India.
[10] Nisha Agrawal , Sanjukta Urma , Sonam Padhan , Ram Ch. Barik, “Indian Agro Based Pest Region Detection by clustering and Pseudo- Color Image Processing” in International Journal of Engineering Research & Technology (IJET) ISSN:2278-0181.

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