Speech Analysis and Tools in L2 Pronunciation Acquisition

Dear Colleagues,

Speech analysis techniques and tools are increasingly used within L2 pronunciation learning and teaching studies. They have been extensively used in research on the acquisition of L2 speech patterns to explore L2 perception and production. They are now the norm within this domain, and include spectral measures such as vowel formants, temporal measures such as voice onset time (VOT), as well as articulatory measures such as ultrasound tongue imaging (UTI), electroglottography (EGG) and electromagnetic articulography (EMA). However, even classical acoustic measurements such as vowel formants may pose challenges when applied to L2 speech; for example, Ferragne (2013) advises against the automatic extraction of formants for L2 data since realisations may deviate considerably from the expected target; the automatic extraction of suprasegmental parameters, such as duration, pitch and intensity, may be more robust. Additionally, many available speech tools, such as automatic aligners, are problematic when used with L2 data (Bailly & Martin, 2013).

Speech analysis is no longer restricted to studies on the acquisition of L2 sounds; recently, scholars have started introducing such tools into the classroom, usually to provide visual reinforcement for target pronunciation patterns, or to enable learners to focus on proprioception and self-correction. Among other tools, pitch visualisation has been used in the classroom to teach L2 intonation patterns (Herment, 2018) or tones (Chen, 2022), with the aim of illustrating target-like pitch contours or the pitch curve for learners’ own realisations. Similarly, visualisations of VOT have been effectively used in teaching interventions (Olson & Offerman, 2021) and to provide online pronunciation feedback via the Moodle platform (Wilson, 2008). The use of automatic formant plots to provide feedback on L2 vowel pronunciation was found to be too complex using technology available less than twenty years ago (Setter & Jenkins, 2005), but recent studies have reported the beneficial effects (Rehman & Das, 2020) of advances in speech analysis tools. Among articulatory techniques, many recent studies have reported benefits of using ultrasound tongue imaging (UTI) to teach segmental contrasts involving different tongue configurations for various classes of L2 languages (Gick et al. 2008; Pillot-Loiseau et al., 2015; Sisinni et al., 2016).

Speech analysis techniques have also been used to develop L2 Computer-Assisted Pronunciation Teaching (CAPT) software, designed to provide corrective automatic scoring and/or feedback, both at the segmental (Saleh & Gilakjani, 2021) and prosodic (Schwab & Goldman, 2018) levels. Many of these tools are based on acoustic measurements of L2 speech. However, even in this case, specific issues arise; for example, should CAPT systems provide generalised or customised feedback to learners (Rogerson-Revell, 2021)? Should CAPT systems be based on a specific native model used as the target reference (e.g., Southern British English, General American English, etc.), a language-independent set of properties designed to reflect L2 speech comprehensibility (cf. Mairano et al. 2019), or a combination of both? Moreover, should they use predefined expert features such as voice onset time and vowel formants (which can be used to provide precise feedback to learners), or should they use machine learning-based approaches?

The goal of this Special Issue is to showcase the state of the art of speech analysis tools and techniques by compiling fundamental studies on L2 speech acquisition, as well as studies with an applied perspective that use speech analysis techniques and tools to teach and/or evaluate L2 production or perception. We welcome contributions on a range of topics, including the following:

• Innovative speech analysis techniques, methodologies or tools to study the acquisition of L2 speech patterns (production and/or perception), or discussions of the limits of specific L1-designed tools and methodologies for studying L2 speech data;
• The development and/or use of speech analysis tools (acoustic or articulatory) in the context of L2 classrooms to improve learners’ pronunciation;
• Innovations in the field of CAPT software for L2 pronunciation feedback and/or scoring.

We request that authors initially submit a proposed title and an abstract of 400–600 words summarising their intended contribution. Please send submissions to the Guest Editors ([email protected] and [email protected]) and to the Languages editorial office ([email protected]). Abstracts will be reviewed by the Guest Editors to assess their relevance to the Special Issue. Full manuscripts will undergo double-blind peer-review.

• Abstract Submission Deadline: 30 January 2023
• Max length of articles: 7000 words (excl. bibliography)

References

Ballier, N., & Martin, P. (2013) Developing corpus interoperability for phonetic investigation of learner corpora. In: A. Diaz-Nergillo, N. Ballier, & P. Thompson (Eds) Automatic Treatment and Analysis of Learner Corpus Data (pp. 151-168). Amsterdam: John Benjamins.

Chen, M. (2022). Computer-aided feedback on the pronunciation of Mandarin Chinese tones: using Praat to promote multimedia foreign language learning. Computer Assisted Language Learning, 1-26.

Ferragne, E. (2013) Automatic suprasegmental parameter extraction in learner corpora. In: A. Diaz-Nergillo, N. Ballier, & P. Thompson (Eds) Automatic Treatment and Analysis of Learner Corpus Data (pp. 151-168). Amsterdam: John Benjamins.

Gick, B., Bernhardt, B., Bacsfalvi, P., & Wilson, I. (2008). Ultrasound imaging applications in second language acquisition. In J. G. Hansen Edwards and M. L. Zampini (eds.), Phonology and Second Language Acquisition (pp. 309-322). Amsterdam: John Benjamins.

Herment, S. (2018). Apprentissage et enseignement de la prosodie : l’importance de la visualisation. Revue française de linguistique appliquée, 23(1), 73-88.

Mairano, P., Bouzon, C., Capliez, M., & De Iacovo, V. (2019) Acoustic distances, Pillai scores and LDA classification scores as metrics of L2 comprehensibility and nativelikeness. Proc. of ICPhS2019 (International Congress of Phonetic Sciences) (pp. 1104-1108), Melbourne (Australia), 5-9 August 2019.

Olson, D. J., & Offerman, H. M. (2021). Maximizing the effect of visual feedback for pronunciation instruction: A comparative analysis of three approaches. Journal of Second Language Pronunciation, 7(1), 89-115.

Pillot-Loiseau, C., Kamiyama, T., & Antolík, T. K. (2015). French/y/-/u/contrast in Japanese learners with/without ultrasound feedback: vowels, non-words and words. In Proceedings of the International Congress of Phonetic Sciences (ICPhS), Glasgow (UK), 10-15 August 2015, 1-5.

Rehman, I., & Das, A. (2020). Real-time visual acoustic feedback for non-native vowel production training. The Journal of the Acoustical Society of America, 148(4), 2657-2657.

Rogerson-Revell, P. M. (2021). Computer-assisted pronunciation training (CAPT): Current issues and future directions. RELC Journal, 52(1), 189-205.

Saleh, A. J., & Gilakjani, A. P. (2021). Investigating the impact of computer-assisted pronunciation teaching (CAPT) on improving intermediate EFL learners’ pronunciation ability. Education and Information Technologies, 26(1), 489-515.

Schwab, S. & Goldman, J.-P. (2018). MIAPARLE: Online training for the discrimination and production of stress contrasts, Proceeding of 9th Speech Prosody Conference (pp. 572-576), Poznan (Poland), 13-16 June 2018.

Setter, J. & Jenkins, J. (2005) State-of-the-art review article: Pronunciation. Language Teaching, 38, 1-17.

Sisinni, B., d’Apolito, S., Fivela, B. G., & Grimaldi, M. (2016). Ultrasound articulatory training for teaching pronunciation of L2 vowels. In Proceedings of ICT for language learning (pp. 265-270).

Wilson, I. (2008). Using Praat and Moodle for teaching segmental and suprasegmental pronunciation. In Proceedings of the 3rd international WorldCALL Conference: Using Technologies for Language Learning (pp. 112-115).

Dr. Paolo Mairano
Dr. Sandra Schwab
Guest Editors

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• speech analysis
• speech tools
• L2 acquisition
• L2 pronunciation
• L2 teaching
• CAPT