Automatic detection of topic boundaries and keywords in arbitrary speech using incremental reference interval-free continuous DP
Automatic detection of topic boundaries and keywords in arbitrary speech using incremental reference interval-free continuous DP
复制标题
使用增量参考无区间连续DP自动检测任意语音中的主题边界和关键词
DOI：
10.1109/icslp.1996.608016
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发表时间：
1996
期刊：
影响因子：
--
通讯作者：
R. Oka
中科院分区：
文献类型：
--
作者：
Jiro Kiyama;Y. Itoh;R. Oka
我们提出了一种方法，用于检测任意语音中的主题边界和关键字，既不识别也不韵律处理，旨在引导访问记录的原始语音的内容。这种方法是基于一种普遍的趋势，即在讲话中频繁重复的短语/单词是话语中的主题的特征。因此，它使用语音的语音相似段对（PPSS）来表示语音中的主题。这种方法的优点是与领域和语言无关，并且对说话者和背景噪音的变化具有鲁棒性，因为它不需要预先使用语言或声学模型。使用模拟对话的实验证实了这种方法的良好性能。我们还提出了增量参考区间自由连续动态规划（IRIFCDP）作为上述方法检测语音中的PPSS的算法。IRIFCDP能够有效地检测出与语音同步的PPSS，因此它适合于处理长语音样本。
We propose an approach for detecting topic boundaries and keywords in arbitrary speech, with neither recognition nor prosodic processing, aiming at guide access to the content of recorded raw speech. This approach is based on the general tendency that frequently repeated phrases/words in speech are characteristic of topics in discourse. So it uses pairs of phonetically similar segments (PPSSs) of speech to represent topics in speech. This approach has the advantage of being domain and language independent and robust against variations in the speaker and background noise, as it needs neither a language nor acoustic model in advance. Experiments using simulated dialogues confirmed the good performance of this approach. We also propose Incremental Reference Interval Free Continuous Dynamic Programming (IRIFCDP) as an algorithm for detecting PPSSs in speech for the above method. IRIFCDP can detect PPSSs efficiently in synchronization with the speech, so it is suitable for handling long speech samples.