Abstract:
This study proposes a methodology to find the interest
levels of two speakers in a conversation. The ANN-HMM approach-a hybrid
method is adopted. The hybrid method uses language input as an additional
parameter in addition to the acoustic features. The language input provides
a measure of classification of the input speech utterance. A combined
classifier is used to make a linear decision on the emotion of the uttered
speech as an arousal or valence. When the decision is fed to the Generative
Factor Analyzed Hidden Markov Model (GFA-HMM) it evidently substantiates
to be a better method with good accuracy rate of classification of whether
the speaker is entangled in the conversation or vice-versa. The proposed
method produced highly satisfactory results for the Linguistic Data Consortium
(LDC) emotional prosody dataset.
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