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Báo cáo khoa học: "Combining Acoustic and Pragmatic Features to Predict Recognition Performance in Spoken Dialogue Systems"

Chia sẻ: Nhung Nhung | Ngày: | Loại File: PDF | Số trang:8

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Báo cáo khoa học: "Combining Acoustic and Pragmatic Features to Predict Recognition Performance in Spoken Dialogue Systems"

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We use machine learners trained on a combination of acoustic confidence and pragmatic plausibility features computed from dialogue context to predict the accuracy of incoming n-best recognition hypotheses to a spoken dialogue system. Our best results show a 25% weighted f-score improvement over a baseline system that implements a “grammar-switching” approach to context-sensitive speech recognition.

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Nội dung Text: Báo cáo khoa học: "Combining Acoustic and Pragmatic Features to Predict Recognition Performance in Spoken Dialogue Systems"

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