CENATAV Voice-Group Systems for Albayzin 2018 Speaker Diarization Evaluation Campaign

Abstract

Usually, the environment to record a voice signal is not ideal and, in order to improve the representation of the speaker characteristic space, it is necessary to use a robust algorithm, thus making the representation more stable in the presence of noise. A Diarization system that focuses on the use of robust feature extraction techniques is proposed in this paper. The pre-sented features ( such as Mean Hilbert Envelope Coefficients, Medium Duration Modulation Coefficients and Power Normalization Cepstral Coefficients ) were not used in other Albayzin Challenges. These robust techniques have a common characteristic, which is the use of a Gammatone filter-bank for divid-ing the voice signal in sub-bands as an alternative option to the classical Triangular filter-bank used in Mel Frequency Cepstral Coefficients. The experiment results show a more stable Diarization Error Rate in robust features than in classic features.