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This work aims at investigating and analyzing speaker identification in eachunbiased and biased emotional talking environments based on a classifier calledSuprasegmental Hidden Markov Models (SPHMMs). The first talking environment isunbiased towards any emotion, while the second talking environment is biasedtowards different emotions. Each of these talking environments is made up ofsix distinct emotions. These emotions are neutral, angry, sad, happy, disgustand fear. The investigation and analysis of this work show that speakeridentification performance in the biased talking environment is superior tothat in the unbiased talking environment. The obtained results in this work areclose to those achieved in subjective assessment by human judges.

Speaker Identification Investigation and Analysis in Unbiased and Biased Emotional Talking Environments