As a branch of artificial intelligence, automated speech recognition (ASR) technology is increasingly used to detect speech, process it to text, and derive the meaning of natural language for various learning and assessment purposes. ASR inaccuracy may pose serious threats to valid score interpretations and fair score use for all when it is…

As a result of the fact that judgments of non-native speech are closely tied to social biases, oral proficiency ratings are susceptible to error because of rater background and social attitudes. In the present study we seek first to estimate the variance attributable to rater background and attitudinal variables on novice raters' assessments of L2…

This article reports on an investigation of the role raters' language background plays in raters' assessment of test takers' speaking ability. Specifically, this article examines differences between American and Indian raters in their scores and scoring processes when rating Indian test takers' responses to the Test of English as a Foreign…