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Wireless Personal Communications
Erschienen in: Wireless Personal Communications 4/2019

26.04.2019

An Algorithm to Identify Syllable from a Visual Speech Recognition System

verfasst von: J. Subhashini, C. Manoj Kumar

Erschienen in: Wireless Personal Communications | Ausgabe 4/2019

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Abstract

This paper is to propose a highly efficient and reliable real time communication system for speech impaired people to communicate and converse in an effective manner. The main idea deals with an algorithm to identify the word from a visual speech input disregard with its acoustic property. The non-acoustic speech is captured through a source and given as an input in the form of image frames then classified to obtain the desired form of output. The input given in the visual form deals with mouth postures. The network is structured to identify the speech in form of syllables. Convolution Neural Network, a deep learning technique is used as its classifier. A database is created especially for this algorithm and are aligned within in the form of class and subsets.
Vorheriger Artikel Feature Extraction Methods in Language Identification: A Survey
Nächster Artikel Scalable Models for Redundant Data Flow Analysis in Online Social Networks

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Metadaten
Titel
An Algorithm to Identify Syllable from a Visual Speech Recognition System
verfasst von
J. Subhashini
C. Manoj Kumar
Publikationsdatum
26.04.2019
Verlag
Springer US
Erschienen in
Wireless Personal Communications / Ausgabe 4/2019
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-019-06374-2

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