Pitch-based emphasis detection for segmenting speech recordings

B. Arons
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引用次数: 60

Abstract

This paper describes a technique to automatically locate emphasized segments of a speech recording based on pitch. These salient portions can be used in a variety of applications, but were originally designed to be used in an interactive system that enables high-speed skimming and browsing of speech recordings. Previous techniques to detect emphasis have used Hidden Markov Models; emphasized regions in close temporal proximity were found to successfully create useful summaries of the recordings. The new research described herein presents a sim pler technique to detect salient segments and summarize a recording without using statistical models that require large amounts of training data. The algorithm adapts to the pitch range of a speaker, then automatically selects the regions of highest pitch activity as a measure of emphasis.
基于音高的语音切分重点检测
本文介绍了一种基于音高自动定位语音录音中重音片段的技术。这些突出的部分可以用于各种应用程序,但最初的设计是用于交互式系统,使高速略读和浏览语音记录。以前检测重点的技术使用了隐马尔可夫模型;在时间上接近的强调区域被发现成功地创建了有用的录音摘要。本文描述的新研究提出了一种更简单的技术来检测突出部分并总结记录,而不使用需要大量训练数据的统计模型。该算法适应说话者的音高范围,然后自动选择最高音高活动的区域作为强调的度量。
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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