RT info:eu-repo/semantics/article T1 Automatic speech recognition (ASR) systems applied to pronunciation assessment of L2 Spanish for Japanese speakers A1 Tejedor García, Cristian A1 Cardeñoso Payo, Valentín A1 Escudero Mancebo, David K1 Automatic speech recognition K1 Computer assisted instruction K1 Educational technology K1 Enseñanza - Evaluación - Metodología K1 Educación - Evaluación K1 Innovative learning environments K1 Machine learning K1 Enseñanza de idiomas K1 Español (Lengua) - pronunciación K1 Automatic speech recognition (ASR) K1 Automatic assessment tools K1 Computer-assisted pronunciation training (CAPT) K1 5312.04 Educación K1 5701.11 Enseñanza de Lenguas AB 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. PB MDPI SN 2076-3417 YR 2021 FD 2021 LK https://uvadoc.uva.es/handle/10324/59491 UL https://uvadoc.uva.es/handle/10324/59491 LA eng NO Applied Sciences, 2021, Vol. 11, Nº. 15, 6695 NO Producción Científica DS UVaDOC RD 17-jul-2024