Paper: Computing and Evaluating Syntactic Complexity Features for Automated Scoring of Spontaneous Non-Native Speech

ACL ID P11-1073
Title Computing and Evaluating Syntactic Complexity Features for Automated Scoring of Spontaneous Non-Native Speech
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2011
Authors

This paper focuses on identifying, extracting and evaluating features related to syntactic complexity of spontaneous spoken responses as part of an effort to expand the current feature set of an automated speech scoring system in order to cover additional aspects considered important in the construct of communicative competence. Our goal is to find effective features, se- lected from a large set of features proposed previously and some new features designed in analogous ways from a syntactic complexity perspective that correlate well with human rat- ings of the same spoken responses, and to build automatic scoring models based on the most promising features by using machine learning methods. On human transcriptions with manually annotated clause and sentence boundaries, ou...