Improving Dialogue Act Classification for Spontaneous Arabic Speech and Instant Messages at Utterance Level
AbdelRahim Elmadany, Sherif Mahdy Abdou, Mervat H. Gheith · 2018
The ability to model and automatically detect dialogue act is an important step toward understanding spontaneous speech and Instant Messages.However, it has been difficult to infer a dialogue act from a surface utterance because it highly depends on the context of the utterance and speaker linguistic knowledge; especially in Arabic dialects.This paper proposes a statistical dialogue analysis model to recognize utterance's dialogue acts using a multi-classes hierarchical structure.The model can automatically acquire probabilistic discourse knowledge from a dialogue corpus were collected and annotated manually from multi-genre Egyptian call-centers.Extensive experiments were conducted using Support Vector Machines classifier to evaluate the system performance.The results attained in the term of average F-measure scores of 0.912; showed that the proposed approach has moderately improved F-measure by approximately 20%.