Automatic summarization of voicemail messages using lexical and prosodic features

K. Koumpis, S. Renals
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引用次数: 77

Abstract

This aticle presents trainable methods for extracting principal content words from voicemail messages. The short text summaries generated are suitable for mobile messaging applications. The system uses a set of classifiers to identify the summary words with each word described by a vector of lexical and prosodic features. We use an ROC-based algorithm, Parcel, to select input features (and classifiers). We have performed a series of objective and subjective evaluations using unseen data from two different speech recognition systems as well as human transcriptions of voicemail speech.
自动总结语音邮件信息使用词汇和韵律的特点
本文提出了一种可训练的语音留言主要内容词提取方法。生成的简短文本摘要适用于移动消息传递应用程序。该系统使用一组分类器来识别总结词,每个词由词汇和韵律特征向量描述。我们使用基于roc的算法Parcel来选择输入特征(和分类器)。我们使用来自两种不同语音识别系统的未见数据以及语音邮件语音的人工转录进行了一系列客观和主观评估。
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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