ABSTRACT
Automatic speech recognition (ASR) technology affords language learners the ability to evaluate their pronunciation accuracy by comparing their intended spoken output with the transcribed text produced by ASR-based dictation applications. However, earlier dictation tools were criticized for producing low level recognition rates for non-native speech. Further investigation on the transcription accuracy of new ASR dictation tools for non-native speech is therefore necessary. This study aimed to evaluate the accuracy of three modern ASR dictation software programs with young Taiwanese learners of English. Capabilities of these ASR applications were also explored by assessing whether the transcription accuracy of high and low proficiency learners’ can be differentiated. Thirty junior high school students dictated the same 60 sentences used in Derwing et al.’s (2000) original dictation study, and their outputs were further analyzed. The results indicated that the transcription accuracy rates of high proficiency learners were comparable to the accuracy rates of native English speakers in previous studies, suggesting that current dictation programs have become more accurate in transcribing non-native speech. Results also show that low proficiency learners’ accuracy rates were significantly lower compared to high proficiency learners, indicating that the programs were able to differentiate proficient and less proficient learners.
Acknowledgments
The authors would like to show their sincere gratitude to Dr. Tracey Derwing and Dr. Murray Munro for providing the original 60 sentences used in the Derwing et al. (Citation2000) study, as well as permitting the implementation of the sentences into this conceptual replication research.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Additional information
Notes on contributors
Kuo-Wei Kyle Lai
Kyle Kuo-Wei Lai is a doctoral student at National Taiwan Normal University, Taipei, Taiwan, Republic of China. His research interests include computer-assisted language learning and digital game-based language learning.
Hao-Jan Howard Chen
Howard Hao-Jan Chen (Ph.D, University of Pennsylvania) is Professor of English Department at National Taiwan Normal University, Taipei, Taiwan. Professor Chen has extensive experiences developing various CALL websites and he also published several papers in CALL Journal, ReCALL Journal and several related language learning journals. His research interests include computer-assisted language learning, corpus research, and second language acquisition. He is now developing and maintaining a large English Learning website, Cool English, serving 600,000 elementary and secondary school students in Taiwan.