Abstract: This paper describes the ATVS-UAM systems submitted to the Audio Segmentation and Speaker Diarization Albayzin 2010 Evaluation. The ATVS-UAM audio segmentation system is based on a 5-GMM-MMI-state HMM model. Testing utterances are aligned with the model by means of the Viterbi algorithm. Spurious changes in the state sequence were removed by mode-filtering step. Finally, too sort segments were removed. The ATVS-UAM speaker diarization system is a novelty approach based on the cosine distance clustering of the Total Variability speech factors -the so-called iVectors- performed in two steps, followed by a Viterbi decodification of the probabilities based on the distances between the candidate speaker centroids and the iVectors stream.
Index Terms: audio segmentation, speaker diarization, viterbi, factor analysis, maximum mutual information.