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Proceedings Paper

Support vector machine and mel frequency Cepstral coefficient based algorithm for hand gestures and bidirectional speech to text device
Author(s): Jessie R. Balbin; Dionis A. Padilla; Janette C. Fausto; Ernesto M. Vergara Jr.; Ramon G. Garcia; Bethsedea Joy S. Delos Angeles; Neil John A. Dizon; Mark Kevin N. Mardo
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Paper Abstract

This research is about translating series of hand gesture to form a word and produce its equivalent sound on how it is read and said in Filipino accent using Support Vector Machine and Mel Frequency Cepstral Coefficient analysis. The concept is to detect Filipino speech input and translate the spoken words to their text form in Filipino. This study is trying to help the Filipino deaf community to impart their thoughts through the use of hand gestures and be able to communicate to people who do not know how to read hand gestures. This also helps literate deaf to simply read the spoken words relayed to them using the Filipino speech to text system.

Paper Details

Date Published: 8 February 2017
PDF: 6 pages
Proc. SPIE 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016), 102250M (8 February 2017); doi: 10.1117/12.2266986
Show Author Affiliations
Jessie R. Balbin, Mapua Institute of Technology (Philippines)
Dionis A. Padilla, Mapua Institute of Technology (Philippines)
Janette C. Fausto, Mapua Institute of Technology (Philippines)
Ernesto M. Vergara Jr., Mapua Institute of Technology (Philippines)
Ramon G. Garcia, Mapua Institute of Technology (Philippines)
Bethsedea Joy S. Delos Angeles, Mapua Institute of Technology (Philippines)
Neil John A. Dizon, Mapua Institute of Technology (Philippines)
Mark Kevin N. Mardo, Mapua Institute of Technology (Philippines)

Published in SPIE Proceedings Vol. 10225:
Eighth International Conference on Graphic and Image Processing (ICGIP 2016)
Yulin Wang; Tuan D. Pham; Vit Vozenilek; David Zhang; Yi Xie, Editor(s)

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