Topic-Segmentation Of Dialogue
نویسندگان
چکیده
We introduce a novel topic segmentation approach that combines evidence of topic shifts from lexical cohesion with linguistic evidence such as syntactically distinct features of segment initial and final contributions. Our evaluation shows that this hybrid approach outperforms state-of-the-art algorithms even when applied to loosely structured, spontaneous dialogue. Further analysis reveals that using dialogue exchanges versus dialogue contributions improves topic segmentation quality.
منابع مشابه
Museli: A Multi-Source Evidence Integration Approach to Topic Segmentation of Spontaneous Dialogue
We introduce a novel topic segmentation approach that combines evidence of topic shifts from lexical cohesion with linguistic evidence such as syntactically distinct features of segment initial contributions. Our evaluation demonstrates that this hybrid approach outperforms state-of-the-art algorithms even when applied to loosely structured, spontaneous dialogue.
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