Title :
Evolutionary discriminative speaker adaptation
Author :
Selouani, Sid-Ahmed
Author_Institution :
LARIHS Lab., Univ. de Moncton, Shippagan, NB, Canada
Abstract :
This paper presents a new evolutionary-based approach that aims at investigating more solutions while simplifying the speaker adaptation process. In this approach, a single global transformation set of parameters is optimized by genetic algorithms using a discriminative objective function. The goal is to achieve accurate speaker adaptation whatever the amount of available adaptive data. Experiments using the ARPA-RM database demonstrate the effectiveness of the proposed method.
Keywords :
evolutionary computation; genetic algorithms; speaker recognition; ARPA-RM database; discriminative objective function; evolutionary discriminative speaker adaptation; evolutionary-based approach; genetic algorithms; Adaptation models; Genetic algorithms; Hidden Markov models; Optimization; Training; Transforms; Vectors;
Conference_Titel :
Automatic Speech Recognition and Understanding (ASRU), 2011 IEEE Workshop on
Conference_Location :
Waikoloa, HI
Print_ISBN :
978-1-4673-0365-1
Electronic_ISBN :
978-1-4673-0366-8
DOI :
10.1109/ASRU.2011.6163924