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This paper presents a novel bilingual model modification approach to improve nonnative speech recognition accuracy when the variations of accented pronunciations occur. Each state of baseline nonnative acoustic model is modified with several candidate states from the auxiliary acoustic model, which is trained on speakers' mother language. State mapping criterion and n-best candidates are investigated,...
The performance of automatic speech recognition decreases drastically for nonnative speakers, especially those who are just beginning to learn foreign language or who have heavy accents. This paper presents a novel bilingual model modification approach to improve nonnative speech recognition via considering these great variations of accented pronunciations. Each state of baseline nonnative acoustic...
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