Third Workshop on Child, Computer and Interaction (WOCCI 2012)

Portland, OR, USA
September 14, 2012

Coherence in Child Language Narratives: A Case Study of Annotation and Automatic Prediction of Coherence

Khairun-nisa Hassanali (1), Yang Liu (1), Thamar Solorio (2)

(1) Computer Science Department, The University of Texas at Dallas, Richardson, TX, USA
(2) Department of Computer and Information Sciences, University of Alabama at Birmingham, Birmingham, AL, USA

Coherence is an important aspect of language ability. In this study, we analyze and annotate child language samples of story retell sessions for coherence and presence of narrative structure and narrative quality constructs. We use these constructs as features and use existing Natural Language Processing (NLP) techniques to build models that automatically predict coherence and language impairment in narratives. Our feature analysis results give us an insight into some of the important narrative quality features such as the use of cognitive inferences and social engagement devices. Our study shows that modeling of coherence in the context of language development in children is promising.

Index Terms: Natural language processing, child language, machine learning, coherence, narrative

Full Paper

Bibliographic reference.  Hassanali, Khairun-nisa / Liu, Yang / Solorio, Thamar (2012): "Coherence in child language narratives: a case study of annotation and automatic prediction of coherence", In WOCCI-2012, 7-12.