Minimizing word error rate in a dyslexic reading-oriented ASR engine using phoneme refinement and alternative pronunciation
Little attention has been given to detecting miscues in the text space read by dyslexic children over an automatic speech recognition (ASR) engine. In an ASR system, the miscues are represented by word error rate (WER) and miscue detection rate (MDR). At all time, WER must be kept low, and MDR high...
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Main Authors: | , |
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Format: | Book Section |
Language: | English |
Published: |
IATED publication
2010
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Subjects: | |
Online Access: | http://repo.uum.edu.my/1339/1/Abrack_view_Zulaikha%2C_J..pdf http://repo.uum.edu.my/1339/ http://www.iated.org |
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Institution: | Universiti Utara Malaysia |
Language: | English |