Research on Automatic Speaker Recognition Based on Speech Clustering

A novel approach of extracting speaker features based on speech clustering technology which employs both speaker´s personality and speech cues is proposed in this work for speaker recognition. Specifically, the speech clustering-based approach is first applied before speaker feature extraction and multi-feature which is extracted respectively from the distinct clusters based on speech clustering is combined as a speaker multi-feature. Those two information cues including speaker´s personality and speech are then effectively integrated using the multi-feature for achieving more robust results. The experiments show that using the template matching method the recognition rate with the multi-feature achieve 95.83%, which is 6.48% increase than the recognition accuracy with the long-term average feature. Moreover the average of false acceptance with the multi-feature decreased than the other ordinary features