A Correlation Metric for Speaker Tracking Using Anchor Models
Mikaël Collet, Delphine Charlet, Frédéric Bimbot · 2006
This paper presents an approach for speaker tracking in a large audio database. The system described is based on a speaker segmentation procedure consisting of a detection of statistical ruptures in the speech signal followed by a speaker detection procedure using anchor models. The technique of anchor modelling is presented and a new metric to compare speech segments based on the correlation coefficient is introduced. This novel metric is evaluated and compared to the classical Euclidean and angular metrics for the speaker detection task. Evaluation is carried out on the audio database of the ESTER evaluation campaign for the rich transcription of French broadcast news. The new metric appears to be more efficient than the classical metrics for the task of speaker detection.