  This paper addresses the formulation of a new speaker identification approach
which employs knowledge of emotional content of speaker information. Our
proposed approach in this work is based on a two-stage recognizer that combines
and integrates both emotion recognizer and speaker recognizer into one
recognizer. The proposed approach employs both Hidden Markov Models (HMMs) and
Suprasegmental Hidden Markov Models (SPHMMs) as classifiers. In the
experiments, six emotions are considered including neutral, angry, sad, happy,
disgust and fear. Our results show that average speaker identification
performance based on the proposed two-stage recognizer is 79.92% with a
significant improvement over a one-stage recognizer with an identification
performance of 71.58%. The results obtained based on the proposed approach are
close to those achieved in subjective evaluation by human listeners.
