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- W74970197 abstract "Arguably the most important part of automatically assessing a new reader’s literacy is in verifying his pronunciation of read-aloud target words. But the pronunciation evaluation task is especially difficult in children, non-native speakers, and pre-literates. Traditional likelihood ratio thresholding methods do not generalize easily, and even expert human evaluators do not always agree on what constitutes an acceptable pronunciation. We propose new recognitionand alignment-based features in a decision tree classification framework, along with the use of prior linguistic information and human perceptual evaluations. Our classification methods demonstrate a 91% agreement with the voted results of 20 human evaluators who agree among themselves 85% of the time." @default.
- W74970197 created "2016-06-24" @default.
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- W74970197 date "2006-09-17" @default.
- W74970197 modified "2023-09-27" @default.
- W74970197 title "Pronunciation verification of children²s speech for automatic literacy assessment" @default.
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- W74970197 doi "https://doi.org/10.21437/interspeech.2006-286" @default.
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