Paper: Coherence Modeling for the Automated Assessment of Spontaneous Spoken Responses

ACL ID N13-1101
Title Coherence Modeling for the Automated Assessment of Spontaneous Spoken Responses
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2013
Authors

This study focuses on modeling discourse co- herence in the context of automated assess- ment of spontaneous speech from non-native speakers. Discourse coherence has always been used as a key metric in human scoring rubrics for various assessments of spoken lan- guage. However, very little research has been done to assess a speaker's coherence in auto- mated speech scoring systems. To address this, we present a corpus of spoken responses that has been annotated for discourse coher- ence quality. Then, we investigate the use of several features originally developed for es- says to model coherence in spoken responses. An analysis on the annotated corpus shows that the prediction accuracy for human holistic scores of an automated speech scoring system can be improved by around 10% ...