TOWARD AN UNDERSTANDING OF THE ROLE OF SPEECH RECOGNITION IN NONNATIVE SPEECH ASSESSMENT
Klaus Zechner, Isaac I. Bejar, Ramin Hemat · ETS Research Report Series · 2007
ABSTRACT The increasing availability and performance of computer‐based testing has prompted more research on the automatic assessment of language and speaking proficiency. In this investigation, we evaluated the feasibility of using an off‐the‐shelf speech‐recognition system for scoring speaking prompts from the LanguEdge field test of 2002. We first established the level of agreement between two trained scorers. We then adapted a speech engine to the language backgrounds and proficiency ranges of the speakers and developed a classification and regression tree (CART) for each of five prompts based on features computed from the output of the speech recognizer. In a validation on held‐out data, we found that while our features are not sufficiently comprehensive to adequately score these prompts, collectively these features appear to capture reliably some aspects of speaking proficiency.