广播新闻口语标题自动生成

Proceedings of the first international conference on Human language technology research - HLT '01 Pub Date : 2001-03-18 DOI:10.3115/1072133.1072144

Rong Jin, Alexander Hauptmann

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引用次数: 37

摘要

在本文中，我们使用包含21190个新闻故事的训练集实现了一组标题生成方法，并在包含1006个广播新闻文档的独立测试语料库上对它们进行了评估，将人工转录的结果与自动识别语音的结果进行了比较。我们使用F1和正确顺序的正确标题词的平均数量作为度量。总的来说，结果表明，为语音识别的新闻文档生成标题是可能的，其准确度接近为完美的文本转录生成标题的准确度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Automatic Title Generation for Spoken Broadcast News

In this paper, we implemented a set of title generation methods using training set of 21190 news stories and evaluated them on an independent test corpus of 1006 broadcast news documents, comparing the results over manual transcription to the results over automatically recognized speech. We use both F1 and the average number of correct title words in the correct order as metric. Overall, the results show that title generation for speech recognized news documents is possible at a level approaching the accuracy of titles generated for perfect text transcriptions.

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来源期刊

Proceedings of the first international conference on Human language technology research - HLT '01

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