An automatic speech recognition system for helping visually impaired children to learn Braille

We present an automatic speech recognition (ASR) system which, along with a haptic interface, is aimed at helping preschool children to learn Braille. The ASR algorithm extracts a set of Mel-Frequency Cepstral Coefficients (MFCC) from the speech signal, followed by a Dynamic Time Warping (DTW) appro...

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Bibliographic Details
Published inSymposium of Image, Signal Processing, and Artificial Vision pp. 1 - 4
Main Authors Ramlrez, Melissa, Sotaquira, Miguel, De La Cruz, Alberto, Maria, Esther, Avellaneda, Gustavo, Ochoa, Ana
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2016
Subjects
Haptic interfaces
Heuristic algorithms
Mel frequency cepstral coefficient
Portable computers
Sensitivity
Speech
Speech recognition
Online AccessGet full text
ISSN2329-6259
DOI10.1109/STSIVA.2016.7743335

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Summary:We present an automatic speech recognition (ASR) system which, along with a haptic interface, is aimed at helping preschool children to learn Braille. The ASR algorithm extracts a set of Mel-Frequency Cepstral Coefficients (MFCC) from the speech signal, followed by a Dynamic Time Warping (DTW) approach, thus allowing to recognize vowels pronounced by the user. The ASR algorithm was tested on 9 subjects and its sensitivity was measured in terms of the percentage of true positives. The highest accuracy values were obtained for the a, e, o and u vowels (with hit ratios of 88.8% in all cases), whereas the i vowel exhibited the lowest sensitivity (77.7%). Validation of user interaction with the haptic system is currently underway, and additional testing is needed to determine the potential benefits that this system offers in the context of preschool education in Colombia.
ISSN:2329-6259
DOI:10.1109/STSIVA.2016.7743335