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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.
|Title of host publication||Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on|
|Number of pages||4|
|Publication status||Published - 2012|