Assessing the impact of (Nigerian, Ghanaian, Zimbabwean, Rwandan and Kenyan) accents on English-speaking speech recognition systems
Date
2019
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Abstract
The use of electronic devices such as computers and mobile phones have rapidly increased
over time. Technological powerhouses have inculcated some form of speech recognition in
their devices and as such, the increase in usage of this devices provides the increase in
interaction between humans and speech recognition. Speech recognition involves adequately
transcribing spoken sentences or words into text. This interaction is present all over the world,
Africa inclusively, and the continent with its diverse languages comes with its diverse accents
and pronunciation of words. A successful interaction between humans and speech recognition
involves these systems adequately transcribing the spoken word to the correct text. However,
with these transcriptions, errors are prone to occur due to the fact that, mismatch in accents can
increase the error rate of a speech recognition system by more than 100% [16]. This Thesis
explores to a very large extent the impact that certain African accents such as Nigerian,
Ghanaian, Zimbabwean, Rwandan and Kenyan have on the accuracy and transcriptions made
by English-speaking speech recognition systems. The findings made in this study states that to
a very large extent, the various African accents used in the study does affect the accuracy of
the speech recognition systems used for the study.
Description
Undergraduate thesis submitted to the Department of Computer Science, Ashesi University, in partial fulfillment of Bachelor of Science degree in Management Information Systems, April 2019
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Keywords
speech recognition, African accents, gender, IBM Watson, Google Cloud, Word Error Rate (WER), transription