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While dysarthric speech recognition can be a convenient interface for dysarthric speakers, it is hard to collect enough speech data to overcome the underestimation problem of acoustic models. In addition, there are lots of pronunciation variations in the collected database due to the paralysis of the articulator of dysarthric speakers. Thus, a discriminative training method is proposed for improving...
In this paper, we propose a two-stage lexicon optimization method based on a statistical acoustic confusability measure to generate an optimized lexicon for automatic speech recognition (ASR). It is usual to build a lexicon by using grapheme-to-phoneme (G2P) conversion. However, G2P is often realized by 1-to-N best mapping, which results in the increase of lexicon size. To mitigate this problem, the...
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