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Graphical models for integrating syllabic information

机译:用于整合音节信息的图形模型

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摘要

We present graphical model based methodology that enhances a speech recognizer with information about syllabic segmentations. The segmentations are specified by locations of syllable nuclei, and the graphical models are able to consider these locations as "soft" information. The graphs give improved discrimination between speech and noise when compared to a baseline model. When using locations derived from oracle information an overall improvement is shown, and when the oracle syllable nuclei are augmented with information about lexical stress the methods give additional improvements over locations alone.
机译:我们提出了基于图形模型的方法,通过有关音节分割的信息增强了语音识别器。通过音节核的位置来指定分段,并且图形模型能够将这些位置视为“软”信息。与基线模型相比,这些图可改善语音和噪声之间的区别。当使用从甲骨文信息中得出的位置时,将显示出整体的改进,并且当甲骨文音节核中增加了有关词法重音的信息时,这些方法将对单独的位置进行进一步的改进。

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