Temporal Information in a Binary Framework for Speaker Recognition

Abstract

In recent years a simple representation of a speech excerpt has been proposed, as a binary matrix allowing easy access to the speaker discriminant information. In addition to the time-related abilities of this representation, it also allows the system to work with a temporal information representation based on sequential changes present in the binary representation. A new temporal information is proposed in order to add it to speaker recognition systems. A new specificity selection approach using a mask in the cumulative vector space is also proposed. This aims to increase effectiveness in the speaker binary key paradigm. The experimental validation, done on the NIST-SRE framework, demonstrates the efficiency of the proposed solutions, which shows an EER improvement of 7%. The combination of i-vector and binary approaches, using the proposed methods, showed the complementarity of the discriminatory information exploited by each of them.