In the present study, three groups of interpreter trainees were formed, two experimental groups, i.e., blended prosody instruction (BPI) and computer-assisted prosody training (CAPT), and one control group (CON). In this experiment the participants took part in a four-week teaching program for 16 sessions (60 minutes per session), i.e., 16 hours…

Scholars have argued for the inclusion of different spoken varieties of English in high-stakes listening tests to better represent the global use of English. However, doing so may introduce additional construct-irrelevant variance due to accent familiarity and the shared first language (L1) advantage, which could threaten test fairness. However,…

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…

Examining spoken features across proficiency levels allows researchers to explore the nature of speaking proficiency as it develops. This line of research has thus far primarily focused on adult second language (L2) learners. Using cross-sectional data based on a large-scale language assessment intended for young L2 learners, in this study, we…

The ultimate aim of our research project was to use the Google Web Speech API to automate scoring of elicited imitation (EI) tests. However, in order to achieve this goal, we had to take a number of preparatory steps. We needed to assess how accurate this speech recognition tool is in recognizing native speakers' production of the test items; we…