Improved Voice Activity Detector Based on Stacking Weak Classifiers

A. Stefanidi, A. Priorov, A. Topnikov, Ekaterina Sidorova
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Abstract

The article considers the problem of speech fragments extraction. The authors have brought together a dataset of speech signals VADSpeakersDB. This dataset consists of phonograms recorded with the help of an application for video conferences. The research considers an original algorithm based on the stacking of independent speech activity detectors and compares it with traditional approaches. The solution has a high accuracy of detecting voice fragments-more than 90%.
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基于叠加弱分类器的改进语音活动检测器
本文研究了语音片段的提取问题。作者汇集了一个语音信号数据集VADSpeakersDB。该数据集由在视频会议应用程序的帮助下录制的留声机组成。本研究提出了一种基于独立语音活动检测器叠加的原始算法,并与传统方法进行了比较。该解决方案对语音片段的检测准确率很高,达到90%以上。
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