Extraction of important sentences using F0 information for speech summarization
Extraction of important sentences using F0 information for speech summarization
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利用F0信息提取重要句子进行语音摘要
DOI：
10.21437/icslp.2002-321
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发表时间：
2002
期刊：
影响因子：
--
通讯作者：
Akira Inoue
中科院分区：
文献类型：
--
作者：
Y. Yamashita;Akira Inoue
本文描述了使用 F0 信息的语音摘要。这项工作中的语音摘要是通过从手工转录的文本数据中提取重要句子来实现的。该框架中的重要问题是根据语音波的韵律信息以及书面文本的语言信息对句子重要性进行自动评分。韵律传达非语言信息，例如说话者的意图，并有助于识别重要的语音部分。韵律信息以日语文节单位的F0参数表示，几乎相当于韵律小乐句。比较了六种F0参数与句子重要性的相关性以及提取重要句子的性能。评估结果表明F0参数的引入对于语音摘要是有效的。
This paper describes speech summarization using F0 information. The speech summarization in this work is realized by the extraction of important sentences from text data transcribed by hand. The important problem in this framework is automatic scoring of sentence importance based on prosodic information from speech wave as well as linguistic information from written text. Prosody conveys non-linguistic information such as speaker’s intention and contributes to identify important parts of speech. The prosodic information is represented in terms of F0 parameters of Japanese bunsetsu unit, which is almost equivalent to a prosodic minor phrase. Six kinds of F0 parameters are compared in regard to correlation to the sentence importance and performance of extracting important sentences. Evaluation results show that introduction of F0 parameters is effective to the speech summarization.