Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

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

Version 1 : Received: 27 June 2021 / Approved: 29 June 2021 / Online: 29 June 2021 (07:31:41 CEST)

A peer-reviewed article of this Preprint also exists.

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. 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.

Journal reference: Appl. Sci. 2021, 11, 6695
DOI: 10.3390/app11156695

Abstract

General–purpose automatic speech recognition (ASR) systems have improved their quality and are being used for pronunciation assessment. However, the assessment of isolated short utterances, as words in minimal pairs for segmental approaches, remains an important challenge, even more 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 of a pre/post-test training experiment spanning four weeks were split into three groups: experimental, in-classroom, and placebo. Experimental group used the CAPT tool described in the paper, which we specially designed for autonomous pronunciation training. Statistically significant improvement for experimental and in-classroom groups is revealed, and moderate correlation values between gASR and kASR results were obtained, beside strong correlations between the post-test scores of both ASR systems with 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.

Subject Areas

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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