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Determining the number of speakers in a meeting using microphone array features

机译:使用麦克风阵列功能确定会议中的发言人人数

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The accuracy of speaker diarisation in meetings relies heavily on determining the correct number of speakers. In this paper we present a novel algorithm based on time difference of arrival (TDOA) features that aims to find the correct number of active speakers in a meeting and thus aid the speaker segmentation and clustering process. With our proposed method the microphone array TDOA values and known geometry of the array are used to calculate a speaker matrix from which we determine the correct number of active speakers with the aid of the Bayesian information criterion (BIC). In addition, we analyse several well-known voice activity detection (VAD) algorithms and verified their fitness for meeting recordings. Experiments were performed using the NIST RT06, RT07 and RT09 data sets, and resulted in reduced error rates compared with BIC-based approaches.
机译:会议中发言者二语化的准确性在很大程度上取决于确定正确的发言者人数。在本文中,我们提出了一种基于到达时间差(TDOA)功能的新颖算法,该算法旨在在会议中找到正确数量的活动发言人,从而帮助发言人进行细分和聚类。通过我们提出的方法,麦克风阵列的TDOA值和阵列的已知几何形状可用于计算扬声器矩阵,然后借助贝叶斯信息标准(BIC)从中确定正确数量的活动扬声器。此外,我们分析了几种著名的语音活动检测(VAD)算法,并验证了它们适合用于会议录音。使用NIST RT06,RT07和RT09数据集进行了实验,与基于BIC的方法相比,可以降低错误率。

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