UGC Approved Journal no 63975

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 6 Issue 6
June-2019
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIRDF06035


Registration ID:
223862

Page Number

174-178

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Title

DEEP NEURAL NETWORK FOR AUTOMATED LIP READING VISUAL SPEECH RECOGNITION

Abstract

Lip Reading is a skill or act of recognizing a speaker’s words by watching the lip movements. It is especially taught to deaf, so that they can communicate effectively. The art of lip reading can be used to help people by enhancing speech recognition in noisy areas, or by security forces in situations where it is necessary to identify a person’s speech when the audio record is not available. Deep Neural Network is a good candidate for recognizing lip-articulated words. The goal of this project is to extract text words from a video input using visual lips tracking and Deep learning techniques.

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"DEEP NEURAL NETWORK FOR AUTOMATED LIP READING VISUAL SPEECH RECOGNITION ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.174-178, June 2019, Available :http://www.jetir.org/papers/JETIRDF06035.pdf

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2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"DEEP NEURAL NETWORK FOR AUTOMATED LIP READING VISUAL SPEECH RECOGNITION ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp174-178, June 2019, Available at : http://www.jetir.org/papers/JETIRDF06035.pdf

Publication Details

Published Paper ID: JETIRDF06035
Registration ID: 223862
Published In: Volume 6 | Issue 6 | Year June-2019
DOI (Digital Object Identifier):
Page No: 174-178
Country: Chennai, Tamil Nadu, India .
Area: Engineering
ISSN Number: 2349-5162


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