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Article

Automatic Speech Recognition (ASR) Systems Applied to Pronunciation Assessment of L2 Spanish for Japanese Speakers

1
Centre for Language and Speech Technology (CLST), Radboud University Nijmegen, P.O. Box 9103, 6500 Nijmegen, The Netherlands
2
ECA-SIMM Research Group, Department of Computer Science, University of Valladolid, 47002 Valladolid, Spain
*
Authors to whom correspondence should be addressed.
This paper is an extended version of our paper published in the conference IberSPEECH2020.
These authors contributed equally to this work.
Academic Editor: José A. González-López
Appl. Sci. 2021, 11(15), 6695; https://doi.org/10.3390/app11156695
Received: 27 June 2021 / Revised: 15 July 2021 / Accepted: 19 July 2021 / Published: 21 July 2021
General-purpose automatic speech recognition (ASR) systems have improved in quality and are being used for pronunciation assessment. However, the assessment of isolated short utterances, such as words in minimal pairs for segmental approaches, remains an important challenge, even more so for non-native speakers. In this work, we compare the performance of our own tailored ASR system (kASR) with the one of Google ASR (gASR) for the assessment of Spanish minimal pair words produced by 33 native Japanese speakers in a computer-assisted pronunciation training (CAPT) scenario. Participants in a pre/post-test training experiment spanning four weeks were split into three groups: experimental, in-classroom, and placebo. The experimental group used the CAPT tool described in the paper, which we specially designed for autonomous pronunciation training. A statistically significant improvement for the experimental and in-classroom groups was revealed, and moderate correlation values between gASR and kASR results were obtained, in addition to strong correlations between the post-test scores of both ASR systems and the CAPT application scores found at the final stages of application use. These results suggest that both ASR alternatives are valid for assessing minimal pairs in CAPT tools, in the current configuration. Discussion on possible ways to improve our system and possibilities for future research are included. View Full-Text
Keywords: automatic speech recognition (ASR); automatic assessment tools; foreign language pronunciation; pronunciation training; computer-assisted pronunciation training (CAPT); automatic pronunciation assessment; learning environments; minimal pairs automatic speech recognition (ASR); automatic assessment tools; foreign language pronunciation; pronunciation training; computer-assisted pronunciation training (CAPT); automatic pronunciation assessment; learning environments; minimal pairs
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MDPI and ACS Style

Tejedor-García, C.; Cardeñoso-Payo, V.; Escudero-Mancebo, D. Automatic Speech Recognition (ASR) Systems Applied to Pronunciation Assessment of L2 Spanish for Japanese Speakers . Appl. Sci. 2021, 11, 6695. https://doi.org/10.3390/app11156695

AMA Style

Tejedor-García C, Cardeñoso-Payo V, Escudero-Mancebo D. Automatic Speech Recognition (ASR) Systems Applied to Pronunciation Assessment of L2 Spanish for Japanese Speakers . Applied Sciences. 2021; 11(15):6695. https://doi.org/10.3390/app11156695

Chicago/Turabian Style

Tejedor-García, Cristian, Valentín Cardeñoso-Payo, and David Escudero-Mancebo. 2021. "Automatic Speech Recognition (ASR) Systems Applied to Pronunciation Assessment of L2 Spanish for Japanese Speakers " Applied Sciences 11, no. 15: 6695. https://doi.org/10.3390/app11156695

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