Advanced voice activity detection on mobile phones by using microphone array and phoneme-specific Gaussian mixture models

B. Popović, E. Pakoci, D. Pekar
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引用次数: 1

Abstract

This paper presents an advanced voice activity detection (VAD) system, developed for mobile Android OS platforms with limited hardware capabilities. The system uses a dual microphone array for noise suppression and a decoder with a constrained grammar for speech detection, where Gaussian mixture models (GMMs) are used together with their acoustic weights and energy in order to increase the robustness of the proposed system. The system is presented as part of the Voice Assistant application for mobile phones, and the results are given on a database that was especially designed for that purpose. The results presented in this paper show a high accuracy even when a large amount of background noise is present.
先进的语音活动检测手机上使用麦克风阵列和音素特定的高斯混合模型
本文介绍了一种先进的语音活动检测(VAD)系统,该系统是在硬件能力有限的移动Android操作系统平台上开发的。该系统使用双麦克风阵列进行噪声抑制,使用具有约束语法的解码器进行语音检测,其中高斯混合模型(gmm)与其声学权重和能量一起使用,以增加所提出系统的鲁棒性。该系统是作为手机语音助手应用程序的一部分呈现的,并且结果是在专门为此目的而设计的数据库中给出的。本文给出的结果表明,即使在存在大量背景噪声的情况下,该方法也具有较高的精度。
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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