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Feature Extraction and Recognition of Hindi Spoken Words using Neural Networks

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Poonam Sharma, Anjali Garg
10.5120/ijca2016909870

Poonam Sharma and Anjali Garg. Feature Extraction and Recognition of Hindi Spoken Words using Neural Networks. International Journal of Computer Applications 142(7):12-17, May 2016. BibTeX

@article{10.5120/ijca2016909870,
	author = {Poonam Sharma and Anjali Garg},
	title = {Feature Extraction and Recognition of Hindi Spoken Words using Neural Networks},
	journal = {International Journal of Computer Applications},
	issue_date = {May 2016},
	volume = {142},
	number = {7},
	month = {May},
	year = {2016},
	issn = {0975-8887},
	pages = {12-17},
	numpages = {6},
	url = {http://www.ijcaonline.org/archives/volume142/number7/24907-2016909870},
	doi = {10.5120/ijca2016909870},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Automatic Speech Recognition System has been a challenging and interesting area of research in last decades. Only a few researchers have worked on Hindi and other Indian languages. In this paper, a Speech Recognition System for Hindi language based on MFCC, PLP and neural networks is proposed and it was observed that the accuracy of the system was better than other conventional methods.

References

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Keywords

Automatic Speech Recognition, Mel frequency Cepstral Coefficient, Predictive Linear Coding