Section: Software

SELORIA

contact : Odile Mella (Odile.Mella@loria.fr).

SELORIA is a toolbox for speaker diarization.

The system contains the following steps:

• Speaker change detection: to find points in the audio stream which are candidates for speaker change points, a distance is computed between two Gaussian modeling data of two adjacent given-length windows. By sliding both windows on the whole audio stream, a distance curve is obtained. A peak in this curve is thus considered as a speaker change point.

• Segment recombination: too many speaker turn points detected during the previous step results in a lot of false alarms. A segment recombination using BIC is needed to recombine adjacent segments uttered by the same speaker.

• Speaker clustering: in this step, speech segments of the same speaker are clustered. Top-down clustering techniques or bottom-up hierarchical clustering techniques using BIC can be used.

• Viterbi re-segmentation: the previous clustering step provides enough data for every speaker to estimate multi-gaussian speaker models. These models are used by a Viterbi algorithm to refine the boundaries between speakers.

• Second speaker clustering step (called cluster recombination): This step uses Universal Background Models (UBM) and the Normalized Cross Likelihood Ratio (NCLR) measure.

This toolbox is derived from mClust designed by LIUM.