Turn Segmentation Into Utterances for Arabic Spontaneous Dialogues and Instant Messages
AbdelRahim Elmadany, Sherif Mahdy Abdou, Mervat H. Gheith · International Journal on Natural Language Computing · 2015
Text segmentation task is an essential processing task for many of Natural Language Processing (NLP) such as text summarization, text translation, dialogue language understanding, among others.Turns segmentation considered the key player in dialogue understanding task for building automatic Human-Computer systems.In this paper, we introduce a novel approach to turn segmentation into utterances for Egyptian spontaneous dialogues and Instance Messages (IM) using Machine Learning (ML) approach as a part of automatic understanding Egyptian spontaneous dialogues and IM task.Due to the lack of Egyptian dialect dialogue corpus the system evaluated by our corpus includes 3001 turns, which are collected, segmented, and annotated manually from Egyptian call-centers.The system achieves F 1 scores of 90.74% and accuracy of 95.98%.