A Preliminary Speech Learning Tool for Improvement of African English Accents
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Date
2014
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE
Abstract
Speech recognition systems emphasise: accent
recognition, recognition system performance through calculation of
word error rate (WER), pronunciation modelling, speech-based
interactions (tone, pitch, volume, background noise, speaker’s gender
and age, speaking speed and quality of recording equipment) and
speech database solutions. However, research into the use of speech
recognition systems for improvement accents is scarcely available. In
this paper, we focus on development of an speech recognition system
for recognizing African English accents and enabling the speakers
improve their English accents. This is achieved by using a dual
speech recognition engine: the first, a multiple accent recogniser
receives African English speech input, classifies it and sends to the
second recogniser that evaluates the speech against standard English
pronunciations. Speech deviations from standard English
pronunciations are captured and read by the system as a way of
supporting the learner to improve his/her reading proficiency.
Preliminary tests indicate that terminologies that are rarely used in
ordinary conversations (e.g. enthusiasm, exuberant, vague, etc) are
most poorly pronounced irrespective of the educational level of the
reader.
Description
Keywords
Speech recognition, African English, Speaker clustering, Acoustic model
Citation
Oyo, B., & Kalema, B. M. (2014, September). A preliminary speech learning tool for improvement of African English accents. In 2014 International Conference on Education Technologies and Computers (ICETC) (pp. 44-48). IEEE.