| Autor: |
Elmadany, AbdelRahim, Abdou, Sherif, Gheith, Mervat |
| Rok vydání: |
2018 |
| Předmět: |
|
| Zdroj: |
11th edition of the Language Resources and Evaluation Conference, 7-12 May 2018, Miyazaki (Japan) |
| Druh dokumentu: |
Working Paper |
| Popis: |
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%. |
| Databáze: |
arXiv |
| Externí odkaz: |
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