Article published in:
Journal of Second Language Pronunciation
Vol. 4:2 (2018) ► pp. 182–207

Directions for the future of technology in pronunciation research and teaching

| University of Calgary
| University of Alberta | Simon Fraser University
| Radboud University
| Michigan State University
| Beuth University Berlin
| Brock University
| Radboud University
| Iowa State University
| Simon Fraser University
| University of Alberta
| Iowa State University
This paper reports on the role of technology in state-of-the-art pronunciation research and instruction, and makes concrete suggestions for future developments. The point of departure for this contribution is that the goal of second language (L2) pronunciation research and teaching should be enhanced comprehensibility and intelligibility as opposed to native-likeness. Three main areas are covered here. We begin with a presentation of advanced uses of pronunciation technology in research with a special focus on the expertise required to carry out even small-scale investigations. Next, we discuss the nature of data in pronunciation research, pointing to ways in which future work can build on advances in corpus research and crowdsourcing. Finally, we consider how these insights pave the way for researchers and developers working to create research-informed, computer-assisted pronunciation teaching resources. We conclude with predictions for future developments.
Keywords: pronunciation, technology, data, computer-assisted pronunciation teaching, research, future directions, automatic speech recognition, intelligibility, comprehensibility
Available under the Creative Commons Attribution-NonCommercial (CC BY-NC) 4.0 license.

For any use beyond this license, please contact the publisher at rights@benjamins.nl.

Published online: 01 February 2019
https://doi.org/10.1075/jslp.17001.obr

Full-text

Directions for the future of technology in pronunciation research and teaching
References

References

Abel, J., Allen, B., Burton, S., Kazama, M., Noguchi, M., Tsuda, A., Yamane, N., & Gick, B.
(2015) Ultrasound-enhanced multimodal approaches to pronunciation teaching and learning. Proceedings of acoustics week in Canada. Canadian Acoustics, 43(3), 124–125.Google Scholar
Abercrombie, D.
(1949) Teaching pronunciation. English Language Teaching, 3, 113–122.Google Scholar
Ballier, N., & Martin, P.
(2016) Speech annotation of learner corpora. In S. Granger, G. Gilquin, & F. Meunier (Eds.), Cambridge handbook of learner corpus research (pp. 107–134). Cambridge: Cambridge University Press. CrossrefGoogle Scholar
Baker, A.
(2014) Exploring teachers’ knowledge of second language pronunciation techniques: Teacher cognitions, observed classroom practices, and student perceptions. TESOL Quarterly, 48, 136–163. CrossrefGoogle Scholar
Boersma, P. & Weenink, D.
(2017) Praat: doing phonetics by computer [Computer program]. Version 6.0.22. Retrieved from http://​www​.fon​.hum​.uva​.nl​/praat/> (15 November 2016).
Bueno Alastuey, M. C.
(2010) Synchronous-voice computer-mediated communication: Effects on pronunciation. CALICO Journal, 28(1), 1–20. CrossrefGoogle Scholar
Catford, J. C.
(1987) Phonetics and the teaching or pronunciation. In J. Morley (Ed.), Current perspectives on pronunciation: Practices anchored in theory (pp. 87–100). Alexandria, VA: TESOL.Google Scholar
Chun, D. M.
(2013) Computer-assisted pronunciation teaching. In C. A. Chapelle (Ed.), Encyclopedia of applied linguistics (pp. 823–834). Malden, MA: Wiley-Blackwell. CrossrefGoogle Scholar
Chun, D. M., Jiang, Y., Meyr, J., & Yang, R.
(2015) Acquisition of L2 Mandarin Chinese tones with learner-created tone visualizations. Journal of Second Language Pronunciation, 1(1), 86–114. CrossrefGoogle Scholar
Cooke, M., Barker, J., & Lecumberri, M. L. G.
(2013) Crowdsourcing in speech perception. In M. Eskenazi, G. -A. Levow, H. Meng, G. Parent, & D. Suendermann (Eds.), Crowdsourcing for speech processing: Applications to data collection, transcription and assessment (pp. 137–172). Chichester: Wiley & Sons.Google Scholar
Cucchiarini, C., & Strik, H.
(2018) Automatic speech recognition for second language pronunciation assessment and training. In O. Kang, R. I. Thomson, & M. J. Murphy (Eds.), pp. 556–569. The Routledge handbook of English pronunciation. London: Routledge.Google Scholar
Cucchiarini, C., Neri, A., & Strik, H.
(2009) Oral proficiency training in Dutch L2: The contribution of ASR-based corrective feedback. Speech Communication, 51(10), 853–863. CrossrefGoogle Scholar
Cucchiarini, C., Strik, H. & Boves, L.
(2000a) Different aspects of expert pronunciation quality ratings and their relation to scores produced by speech recognition algorithm. Speech Communication, 30(2–3), 109–119. CrossrefGoogle Scholar
Cucchiarini, C., Strik, H., & Boves, L.
(2000b) Quantitative assessment of second language learners’ fluency. Journal of the Acoustical Society of America, 107(2), 989–999.Google Scholar
Cucchiarini, C., Strik, H. & Boves, L.
(2002) Quantitative assessment of second language learners’ fluency: Comparisons between read and spontaneous speech. Journal of the Acoustical Society of America, 111(6), 2862–2873. CrossrefGoogle Scholar
Cucchiarini, C., Driesen, J., Van Hamme, H., & Sanders, E.
(2008) Recording speech of children, non-natives and elderly people for HLT applications: The JASMIN-CGN corpus. Proceedings of the 6th International Conference on Language Resources and Evaluation, LREC 2008 (pp. 1445–1450).Google Scholar
Darcy, I., Ewert, D., & Lidster, R.
(2012) Bringing pronunciation instruction back into the classroom: An ESL teachers’ pronunciation “toolbox”. In. J. Levis & K. LeVelle (Eds.), Proceedings of the 3rd Pronunciation in Second Language Learning and Teaching Conference, Sept. 2011 (pp. 93–108). Ames, IA: Iowa State University.Google Scholar
Derwing, T. M., & Munro, M. J.
(2005) Second language accent and pronunciation teaching: A research-based approach. TESOL Quarterly, 39, 379–397. CrossrefGoogle Scholar
(2015) Pronunciation fundamentals: Evidence-based perspectives for L2 teaching. Amsterdam: John Benjamins. CrossrefGoogle Scholar
Do, H., Hussein, H., Mixdorff, H., Jokisch, O., Ding, H., Gao, Q., Wei, S. and Hu, G.
(2012) Evaluation of benefits from a computer-aided pronunciation training system for German learners of Mandarin Chinese. Proceedings of Speech Prosody 2012 (pp. 362–365). Shanghai, China.Google Scholar
Durand, J., Gut, U., & Kristofferson, G.
(Eds.) (2014) Handbook of corpus phonology. Oxford: Oxford University Press.Google Scholar
Eskenazi, M.
(2013) The basics. In M. Eskenazi, G. -A. Levow, H. Meng, G. Parent, & D. Suendermann (Eds.), Crowdsourcing for speech processing: Applications to data collection, transcription and assessment (pp. 11–33). Chichester: Wiley & Sons.Google Scholar
Field, J.
(2005) Intelligibility and the listener: The role of lexical stress. TESOL Quarterly, 39(3), 399–423. CrossrefGoogle Scholar
Foote, J. A., Holtby, A. K., & Derwing, T. M.
(2011) Survey of the teaching of pronunciation in adult ESL programs in Canada, 2010. TESL Canada Journal, 29(1), 1–22. CrossrefGoogle Scholar
Foote, J., & Smith, G.
(2013, September). Is there an app for that? Paper presented at the 5th Pronunciation in Second Language Learning and Teaching Conference, Ames, IA.
Fujisaki, H. & Hirose, K.
(1984) Analysis of voice fundamental frequency contours for declarative sentences of Japanese. Journal of the Acoustical Society of Japan, 5(4), 233–241. CrossrefGoogle Scholar
Gilquin, G.
(2015) From design to collection of learner corpora. In S. Grainger, G. Gilquin, & F. Meunier (Eds.), The Cambridge handbook of learner corpus research (pp. 9–34). Cambridge: Cambridge University Press. CrossrefGoogle Scholar
Granger, S., Gilquin, G., & Meunier, F.
(2016) Introduction: Learner corpus research – past, present and future. In S. Granger, G. Gilquin, & F. Meunier (Eds.), Cambridge handbook of learner corpus research (pp. 1–5). Cambridge: Cambridge University Press. CrossrefGoogle Scholar
Hahn, L. D.
(2004) Primary stress and intelligibility: Research to motivate the teaching of suprasegmentals. TESOL Quarterly, 38(2), 201–223. CrossrefGoogle Scholar
Hahn, M. K.
(2002) The persistence of learned primary phrase stress patterns among learners of English (Unpublished doctoral dissertation). University of Illinois, Urbana-Champaign.Google Scholar
Hardison, D. M.
(2004) Generalization of computer-assisted prosody training: Quantitative and qualitative findings. Language Learning & Technology 8(1), 34–52. Retrieved from http://​llt​.msu​.edu​/vol8num1​/pdf​/hardison​.pdf
(2016, August). Visualizing the gestural and prosodic components of emphasis in multimodal discourse. Paper presented at the International Roundtable on The Role of Technology in L2 Pronunciation Research and Teaching, University of Calgary, Canada.
Hilbert, A., Mixdorff, H., Ding, H., Pfizinger, H., & Jokisch, O.
(2010) Prosodic analysis of accented German by Russian and Chinese learners. Proceedings of Speech Prosody 2010, Chicago, IL.Google Scholar
Hilbert, A., & Mixdorff, H.
(2011) Weiterentwicklung eines Sprachsynthesesystems. In G. Görlitz (Ed.), Nachhaltige Forschung in Wachstumsbereichen Band I (pp. 35–42). Berlin: Logos Verlag.Google Scholar
Hu, W., Qian, Y., Soong, F. K., & Wang, Y.
(2015) Improved mispronunciation detection with deep neural network trained acoustic models and transfer learning based logistic regression classifiers. Speech Communication, 67, 154–166. CrossrefGoogle Scholar
Hussein, H., Do, H. S., Mixdorff, H., Ding, H., Gao, Q., Hu, G., Wei, S., & Chao, Z.
(2011) Mandarin tone perception and production by German learners. Proceedings of the Workshop on Speech and Language Technology in Education (SLaTE), Venice, Italy.Google Scholar
Ingram, J., Mixdorff, H., & Kwon, N.
(2009) Voice morphing and the manipulation of intra-speaker and cross-speaker phonetic variation to create foreign accent continua: A perceptual study. Proceedings of the Workshop on Speech and Language Technology in Education (SLaTE), Wroxall Abbey, England.Google Scholar
Kipp, M.
(2001)  Anvil – A generic annotation tool for multimodal dialogue. Proceedings of the 7th European Conference on Speech Communication and Technology (pp. 1367–1370). Aalborg, Denmark: Eurospeech. Available at http://​www​.anvil​-software​.org/
(2014) ANVIL: A universal video research tool. In J. Durand, U. Gut, & G. Kristofferson (Eds.), Handbook of corpus phonology (pp. 420–436). Oxford: Oxford University Press. CrossrefGoogle Scholar
Lee, J., Jang, J., & Plonsky, L.
(2015) The effectiveness of second language pronunciation instruction: A meta-analysis. Applied Linguistics, 36(3), 345–366. CrossrefGoogle Scholar
Levis, J. M.
(2005) Changing contexts and shifting paradigms in pronunciation teaching. TESOL Quarterly, 39(3), 369–377. CrossrefGoogle Scholar
Levis, J.
(2007) Computer technology in teaching and researching. Annual Review of Applied Linguistics, 27, 184–202. CrossrefGoogle Scholar
Lippi-Green, R.
(2012) English with an accent: Language, ideology, and discrimination in the United States (2nd ed.). London: Routledge. CrossrefGoogle Scholar
Liu, X., Deng, E., Liu, S., et al.
(Eds.) (1981) Shíyòng Hànyŭ Kèbĕn Dì Yī Cè 实用汉语课本第一册 [Practical Chinese Reader, Book I] (pp. i–viii). Beijing: Shangwu yinshuguan (The Commercial Press).Google Scholar
Lively, S. E., Logan, J. S., & Pisoni, D. B.
(1993) Training Japanese listeners to identify English /r/ and /l/. II: The role of phonetic environment and talker variability in learning new perceptual categories. Journal of the Acoustical Society of America, 96, 2076–2087. CrossrefGoogle Scholar
Mackey, A., & Gass, S.
(2005) Second language research: Methodology and design. Mahwah, NJ: Lawrence Erlbaum Associates. Crossref.Google Scholar
MacWhinney, B.
(2000) The CHILDES Project: Tools for analyzing talk (3rd ed.). Mahwah, NJ: Lawrence Erlbaum Associates. Crossref. Retrieved from http://​childes​.talkbank​.org/
Mixdorff, H., & Ingram, J.
(2009) Prosodic analysis of foreign-accented English. Proceedings of Interspeech, Brighton, UK.Google Scholar
Mixdorff, H., Külls, D., Hussein, H., Shu, G., Guoping, H., & Si, W.
(2009) Towards a computer-aided pronunciation training system for German learners of Mandarin. In Proceedings of the Workshop on Speech and Language Technology in Education (SLaTE), Wroxall Abbey, Warwickshire, UK.Google Scholar
Mixdorff, H., & Munro, M. J.
(2013) Quantifying and evaluating the impact of prosodic differences of foreign-accented English. Proceedings of the Workshop on Speech and Language Technology in Education (SLaTE). Grenoble, France.Google Scholar
Motohashi-Saigo, M., & Hardison, D. M.
(2009) Acquisition of L2 Japanese geminates: Training with waveform displays. Language Learning & Technology, 13(2), 29–47. Retrieved from http://​llt​.msu​.edu​/vol13num2​/motohashisaigohardison​.pdf
Munro, M. J., & Derwing, T. M.
(2006) The functional load principle in ESL pronunciation instruction: An exploratory study. System, 34, 520–531. CrossrefGoogle Scholar
Munro, M. J., Derwing, T. M., & Thomson, R. I.
(2015) Setting segmental priorities for English learners: Evidence from a longitudinal study. International Review of Applied Linguistics in Language Teaching, 53(1), 39–60.Google Scholar
Murphy, J.
(1997) Phonology courses offered by MATESOL programs in the US. TESOL Quarterly, 31, 741–764. CrossrefGoogle Scholar
Neri, A., Cucchiarini, C., Strik, H., & Boves, L.
(2002) The pedagogy-technology interface in computer assisted pronunciation training. Computer Assisted Language Learning, 15(5), 441–467. CrossrefGoogle Scholar
Neumeyer, L., Franco, H., Digalakis, V., & Weintraub, M.
(2000) Automatic scoring of pronunciation quality. Speech Communication, 30(2), 83–93.Google Scholar
O’Brien, M. G.
(2011) Teaching and assessing pronunciation with computer technology. In N. Arnold & L. Ducate (Eds.), Present and Future Promises of CALL: From Theory and Research to New Directions in Language Teaching (2nd ed.) (pp. 375–406). San Marcos, TX: CALICO Monograph Series.Google Scholar
Okuno, T., & Hardison, D. M.
(2016) Perception-production link in L2 Japanese vowel duration: Training with technology. Language Learning & Technology, 20, 61–80. Retrieved from http://​llt​.msu​.edu​/issues​/june2016​/okunohardison​.pdf
Olson, D. J.
(2014) Benefits of visual feedback on segmental production in the L2 classroom. Language Learning & Technology, 18(3), 173–192. Retrieved from http://​llt​.msu​.edu​/issues​/october2014​/olson​.pdf
Pennington, M. C.
(1999) Computer-aided pronunciation pedagogy: Promise, limitations, directions. Computer Assisted Language Learning, 12(5), 427–440. CrossrefGoogle Scholar
Pennington, M. C., & Ellis, N. C.
(2000) Cantonese speakers’ memory for English sentences with prosodic cues. The Modern Language Journal, 84(3), 372–389.Google Scholar
Qian, M., Chukharev-Hudalainen, E., & Levis, J.
(2018) A system for adaptive high-variability segmental-perceptual training: Implementation, effectiveness, and transfer. Language Learning and Technology, (22), 69–96.Google Scholar
Qian, X., Meng, H., Soong, F.
(2012) The use of DBN-HMMs for mispronunciation detection and diagnosis in L2 English to support computer-aided pronunciation training. Proceedings of Interspeech 2012 (pp. 775–778), Portland, OR.Google Scholar
Rose, Y., & MacWhinney, B.
(2014) The PhonBank project: Data and software-assisted methods for the study of phonology and phonological development. In J. Durand, U. Gut, & G. Kristoffersen (Eds.), The Oxford handbook of corpus phonology (pp. 308–401). Oxford: Oxford University Press.Google Scholar
Smith, B. L., & Hayes-Harb, R.
(2011) Individual differences in the perception of final consonant voicing among native and non-native speakers of English. Journal of Phonetics, 39, 115–120. CrossrefGoogle Scholar
Staples, S.
(2015) Spoken corpora. In D. Biber & R. Reppen (Eds.), The Cambridge handbook of English corpus linguistics (pp. 271–291). Cambridge: Cambridge University Press.Google Scholar
Strik, H.
(2012) ASR-based systems for language learning and therapy. International Symposium on Automatic Detection of Errors in Pronunciation Training (IS-Adept). KTH, Stockholm, Sweden 6–8 June.Google Scholar
Strik, H., Colpaert, J., Van Doremalen, J., & Cucchiarini, C.
(2012) The DISCO ASR-based CALL system: Practicing L2 oral skills and beyond. Proceedings of the Conference on International Language Resources and Evaluation (LREC 2012), Istanbul, May.Google Scholar
Strik, H., & Cucchiarini, C.
(2014) On automatic phonological transcription of speech corpora. In J. Durand, U. Gut, & G. Kristofferson (Eds.), The Oxford handbook of corpus phonology. Oxford: Oxford University Press. CrossrefGoogle Scholar
Strik, H., Truong, K., de Wet, F., & Cucchiarini, C.
(2009) Comparing different approaches for automatic pronunciation error detection. Speech Communication, 51(10), 845–852. CrossrefGoogle Scholar
Sweet, H.
(1900) The practical study of languages: A guide for teachers and learners. New York, NY: Henry Holt & Co.Google Scholar
Thomson, R. I.
(2011) Computer assisted pronunciation training: Targeting second language vowel perception improves pronunciation. CALICO Journal, 28, 744–765. CrossrefGoogle Scholar
(2016) Does training to perceive L2 English vowels in one phonetic context transfer to other phonetic contexts? Proceedings of the annual conference of the Canadian Acoustics Association. Canadian Acoustics, 44(3), 198–199.Google Scholar
(2017) English Accent Coach [Computer program]. Version 2.3. Retrieved from www​.englishaccentcoach​.com
Thomson, R. I., & Derwing, T. M.
(2015) The effectiveness of L2 pronunciation instruction: A narrative review. Applied Linguistics, 36(3), 326–344. CrossrefGoogle Scholar
(2016) Is phonemic training using nonsense or real words more effective? In J. Levis, H. Le, I. Lucic, E. Simpson, & S. Vo (Eds.). Proceedings of the 7th Pronunciation in Second Language Learning and Teaching Conference, Oct. 2015 (pp. 88–97). Ames, IA: Iowa State University.Google Scholar
Trouvain, J., & Gut, U.
(Eds.) (2007) Non-native prosody: Phonetic description and teaching practice. Berlin: Mouton de Gruyter.Google Scholar
Van Doremalen, J.
(2014) Developing automatic speech recognition-enabled language learning applications: from theory to practice. Evaluating automatic speech recognition-based language learning systems: a case study (Unpublished PhD dissertation). Radboud University, Nijmegen.Google Scholar
Van Doremalen, J., Boves, L., Colpaert, J., Cucchiarini, C., & Strik, H.
(2016) Evaluating automatic speech recognition-based language learning systems: A case study. Computer Assisted Language Learning, 29(4), 833–851. CrossrefGoogle Scholar
Van Doremalen, J., Cucchiarini, C., & Strik, H.
(2010) Optimizing automatic speech recognition for low-proficient non-native speakers. EURASIP Journal on Audio, Speech, and Music Processing 2009. CrossrefGoogle Scholar
(2013) Automatic pronunciation error detection in non-native speech: the case of vowel errors in Dutch. Journal of the Acoustical Society of America, 134, 1336–1347. CrossrefGoogle Scholar
Weinberger, S. H.
(2017) Speech Accent Archive. George Mason University. Retrieved from http://​accent​.gmu​.edu
Witt, S., & Young, S.
(2000) Phone-level pronunciation scoring and assessment for interactive language learning. Speech Communication, 30(2/3): 95–108. CrossrefGoogle Scholar
Zielinski, B.
(2008) The listener: No longer the silent partner in reduced intelligibility. System, 36, 69–84. CrossrefGoogle Scholar
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