Exploiting Psychological Factors for Interaction Style Recognition in Spoken Conversation

Determining how a speaker is engaged in a conversation is crucial for achieving harmonious interaction between computers and humans. In this study, a fusion approach was developed based on psychological factors to recognize Interaction Style ( <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$IS$</tex> </formula> ) in spoken conversation, which plays a key role in creating natural dialogue agents. The proposed Fused Cross-Correlation Model (FCCM) provides a unified probabilistic framework to model the relationships among the psychological factors of emotion, personality trait ( <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$PT$</tex></formula> ), transient <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex Notation="TeX">$IS$</tex></formula> , and <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex Notation="TeX">$IS$</tex></formula> history, for recognizing <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$IS$</tex></formula> . An emotional arousal-dependent speech recognizer was used to obtain the recognized spoken text for extracting linguistic features to estimate transient <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex Notation="TeX">$IS$</tex></formula> likelihood and recognize <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$PT$</tex></formula> . A temporal course modeling approach and an emotional sub-state language model, based on the temporal phases of an emotional expression, were employed to obtain a better emotion recognition result. The experimental results indicate that the proposed FCCM yields satisfactory results in <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex Notation="TeX">$IS$</tex></formula> recognition and also demonstrate that combining psychological factors effectively improves <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex Notation="TeX">$IS$</tex></formula> recognition accuracy.