自发语音语料库的形态分析

Kiyotaka Uchimoto, Chikashi Nobata, Atsushi Yamada, S. Sekine, H. Isahara
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引用次数: 15

摘要

本文描述了一个用分词和词性等形态学信息标注自发语音语料库的方案。我们使用了一个基于最大熵模型的形态学分析系统,该系统与语料库的领域无关。本文展示了使用该模型所获得的标注精度,并讨论了在标注自发语音语料库时存在的问题。我们还表明,为某一领域的语料库开发的词典有助于提高分析另一领域语料库的准确性。
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Morphological Analysis of the Spontaneous Speech Corpus
This paper describes a project tagging a spontaneous speech corpus with morphological information such as word segmentation and parts-of-speech. We use a morphological analysis system based on a maximum entropy model, which is independent of the domain of corpora. In this paper we show the tagging accuracy achieved by using the model and discuss problems in tagging the spontaneous speech corpus. We also show that a dictionary developed for a corpus on a certain domain is helpful for improving accuracy in analyzing a corpus on another domain.
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