Title :
Efficient iterative mean shift based cosine dissimilarity for multi-recording speaker clustering
Author :
Senoussaoui, Mohammed ; Kenny, P. ; Dumouchel, P. ; Stafylakis, Themos
Author_Institution :
Ecole de Technol. Super. (ETS), Montréal, QC, Canada
Abstract :
Speaker clustering is an important task in many applications such as Speaker Diarization as well as Speech Recognition. Speaker clustering can be done within a single multi-speaker recording (Diarization) or for a set of different recordings. In this work we are interested by the former case and we propose a simple iterative Mean Shift (MS) algorithm to deal with this problem. Traditionally, MS algorithm is based on Euclidean distance. We propose to use the Cosine distance in order to build a new version of MS algorithm. We report results as measured by speaker and cluster impurities on NIST SRE 2008 datasets.
Keywords :
audio recording; iterative methods; speaker recognition; Euclidean distance; MS algorithm; NIST SRE 2008 datasets; cluster impurities; cosine distance; iterative mean shift based cosine dissimilarity; multirecording speaker clustering; single multispeaker recording; speaker diarization; speaker impurities; speech recognition; Clustering algorithms; Euclidean distance; Impurities; Integrated circuits; Kernel; Speaker recognition; Speech; Cluster Impurity; Cosine distance; Mean Shift (MS); Speaker Clustering; Speaker Impurity;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on
Conference_Location :
Vancouver, BC
DOI :
10.1109/ICASSP.2013.6639164
