Paper: Shallow Analysis Based Assessment of Syntactic Complexity for Automated Speech Scoring

ACL ID P14-1123
Title Shallow Analysis Based Assessment of Syntactic Complexity for Automated Speech Scoring
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2014
Authors

Designing measures that capture various aspects of language ability is a central task in the design of systems for auto- matic scoring of spontaneous speech. In this study, we address a key aspect of lan- guage proficiency assessment ? syntactic complexity. We propose a novel measure of syntactic complexity for spontaneous speech that shows optimum empirical per- formance on real world data in multiple ways. First, it is both robust and reliable, producing automatic scores that agree well with human rating compared to the state- of-the-art. Second, the measure makes sense theoretically, both from algorithmic and native language acquisition points of view.