1887
Volume 4, Issue 2
  • ISSN 2215-1931
  • E-ISSN: 2215-194X

Abstract

Abstract

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.

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 license.
Loading

Article metrics loading...

/content/journals/10.1075/jslp.17001.obr
2019-02-01
2019-09-17
Loading full text...

Full text loading...

/deliver/fulltext/jslp.17001.obr.html?itemId=/content/journals/10.1075/jslp.17001.obr&mimeType=html&fmt=ahah

References

  1. 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]
  2. Abercrombie, D.
    (1949) Teaching pronunciation. English Language Teaching, 3, 113–122. 10.1093/elt/III.5.113
    https://doi.org/10.1093/elt/III.5.113 [Google Scholar]
  3. Ballier, N., & Martin, P.
    (2016) Speech annotation of learner corpora. InS. Granger, G. Gilquin, & F. Meunier (Eds.), Cambridge handbook of learner corpus research (pp. 107–134). Cambridge: Cambridge University Press. doi:  10.1017/CBO9781139649414
    https://doi.org/10.1017/CBO9781139649414 [Google Scholar]
  4. Baker, A.
    (2014) Exploring teachers’ knowledge of second language pronunciation techniques: Teacher cognitions, observed classroom practices, and student perceptions. TESOL Quarterly, 48, 136–163. doi:  10.1002/tesq.99
    https://doi.org/10.1002/tesq.99 [Google Scholar]
  5. Boersma, P. & Weenink, D.
    (2017) Praat: doing phonetics by computer [Computer program]. Version 6.0.22. Retrieved from www.fon.hum.uva.nl/praat/ (15November 2016).
  6. Bueno Alastuey, M. C.
    (2010) Synchronous-voice computer-mediated communication: Effects on pronunciation. CALICO Journal, 28(1), 1–20. doi:  10.11139/cj.28.1.1‑20
    https://doi.org/10.11139/cj.28.1.1-20 [Google Scholar]
  7. Catford, J. C.
    (1987) Phonetics and the teaching or pronunciation. InJ. Morley (Ed.), Current perspectives on pronunciation: Practices anchored in theory (pp. 87–100). Alexandria, VA: TESOL.
    [Google Scholar]
  8. Chun, D. M.
    (2013) Computer-assisted pronunciation teaching. InC. A. Chapelle (Ed.), Encyclopedia of applied linguistics (pp. 823–834). Malden, MA: Wiley-Blackwell. doi:  10.1002/9781405198431.wbeal0172
    https://doi.org/10.1002/9781405198431.wbeal0172 [Google Scholar]
  9. 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. doi:  10.1075/jslp.1.1.04chu
    https://doi.org/10.1075/jslp.1.1.04chu [Google Scholar]
  10. Cooke, M., Barker, J., & Lecumberri, M. L. G.
    (2013) Crowdsourcing in speech perception. InM. 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. 10.1002/9781118541241.ch6
    https://doi.org/10.1002/9781118541241.ch6 [Google Scholar]
  11. Cucchiarini, C., & Strik, H.
    (2018) Automatic speech recognition for second language pronunciation assessment and training. InO. Kang, R. I. Thomson, & M. J. Murphy (Eds.), pp.556–569. The Routledge handbook of English pronunciation. London: Routledge.
    [Google Scholar]
  12. 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. doi:  10.1016/j.specom.2009.03.003
    https://doi.org/10.1016/j.specom.2009.03.003 [Google Scholar]
  13. 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. doi:  10.1016/S0167‑6393(99)00040‑0
    https://doi.org/10.1016/S0167-6393(99)00040-0 [Google Scholar]
  14. 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. 10.1121/1.428279
    https://doi.org/10.1121/1.428279 [Google Scholar]
  15. 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. doi:  10.1121/1.428279
    https://doi.org/10.1121/1.428279 [Google Scholar]
  16. 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]
  17. 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]
  18. Derwing, T. M., & Munro, M. J.
    (2005) Second language accent and pronunciation teaching: A research-based approach. TESOL Quarterly, 39, 379–397. doi:  10.2307/3588486
    https://doi.org/10.2307/3588486 [Google Scholar]
  19. (2015) Pronunciation fundamentals: Evidence-based perspectives for L2 teaching. Amsterdam: John Benjamins. doi:  10.1075/lllt.42
    https://doi.org/10.1075/lllt.42 [Google Scholar]
  20. 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]
  21. Durand, J., Gut, U., & Kristofferson, G.
    (Eds.) (2014) Handbook of corpus phonology. Oxford: Oxford University Press.
    [Google Scholar]
  22. Eskenazi, M.
    (2013) The basics. InM. 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. 10.1002/9781118541241.ch2
    https://doi.org/10.1002/9781118541241.ch2 [Google Scholar]
  23. Field, J.
    (2005) Intelligibility and the listener: The role of lexical stress. TESOL Quarterly, 39(3), 399–423. doi:  10.2307/3588487
    https://doi.org/10.2307/3588487 [Google Scholar]
  24. 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. doi:  10.18806/tesl.v29i1.1086
    https://doi.org/10.18806/tesl.v29i1.1086 [Google Scholar]
  25. Foote, J., & Smith, G.
    (2013, September). Is there an app for that?Paper presented at the5th Pronunciation in Second Language Learning and Teaching Conference, Ames, IA.
    [Google Scholar]
  26. 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. doi:  10.1250/ast.5.233
    https://doi.org/10.1250/ast.5.233 [Google Scholar]
  27. Gilquin, G.
    (2015) From design to collection of learner corpora. InS. Grainger, G. Gilquin, & F. Meunier (Eds.), The Cambridge handbook of learner corpus research (pp. 9–34). Cambridge: Cambridge University Press. doi:  10.1017/CBO9781139649414.002
    https://doi.org/10.1017/CBO9781139649414.002 [Google Scholar]
  28. Granger, S., Gilquin, G., & Meunier, F.
    (2016) Introduction: Learner corpus research – past, present and future. InS. Granger, G. Gilquin, & F. Meunier (Eds.), Cambridge handbook of learner corpus research (pp. 1–5). Cambridge: Cambridge University Press. doi:  10.1017/CBO9781139649414.001
    https://doi.org/10.1017/CBO9781139649414.001 [Google Scholar]
  29. Hahn, L. D.
    (2004) Primary stress and intelligibility: Research to motivate the teaching of suprasegmentals. TESOL Quarterly, 38(2), 201–223. doi:  10.2307/3588378
    https://doi.org/10.2307/3588378 [Google Scholar]
  30. Hahn, M. K.
    (2002) The persistence of learned primary phrase stress patterns among learners of English (Unpublished doctoral dissertation). University of Illinois, Urbana-Champaign.
  31. Hardison, D. M.
    (2004) Generalization of computer-assisted prosody training: Quantitative and qualitative findings. Language Learning & Technology 8(1), 34–52. Retrieved from llt.msu.edu/vol8num1/pdf/hardison.pdf
    [Google Scholar]
  32. (2016, August). Visualizing the gestural and prosodic components of emphasis in multimodal discourse. Paper presented at theInternational Roundtable on The Role of Technology in L2 Pronunciation Research and Teaching, University of Calgary, Canada.
    [Google Scholar]
  33. 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]
  34. Hilbert, A., & Mixdorff, H.
    (2011) Weiterentwicklung eines Sprachsynthesesystems. InG. Görlitz (Ed.), Nachhaltige Forschung in Wachstumsbereichen Band I (pp. 35–42). Berlin: Logos Verlag.
    [Google Scholar]
  35. 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. doi:  10.1016/j.specom.2014.12.008
    https://doi.org/10.1016/j.specom.2014.12.008 [Google Scholar]
  36. 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]
  37. 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]
  38. 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 www.anvil-software.org/
    [Google Scholar]
  39. (2014) ANVIL: A universal video research tool. InJ. Durand, U. Gut, & G. Kristofferson (Eds.), Handbook of corpus phonology (pp. 420–436). Oxford: Oxford University Press. doi:  10.1093/oxfordhb/9780199571932.013.024
    https://doi.org/10.1093/oxfordhb/9780199571932.013.024 [Google Scholar]
  40. Lee, J., Jang, J., & Plonsky, L.
    (2015) The effectiveness of second language pronunciation instruction: A meta-analysis. Applied Linguistics, 36(3), 345–366. doi:  10.1093/applin/amu040
    https://doi.org/10.1093/applin/amu040 [Google Scholar]
  41. Levis, J. M.
    (2005) Changing contexts and shifting paradigms in pronunciation teaching. TESOL Quarterly, 39(3), 369–377. doi:  10.2307/3588485
    https://doi.org/10.2307/3588485 [Google Scholar]
  42. Levis, J.
    (2007) Computer technology in teaching and researching. Annual Review of Applied Linguistics, 27, 184–202. doi:  10.1017/S0267190508070098
    https://doi.org/10.1017/S0267190508070098 [Google Scholar]
  43. Lippi-Green, R.
    (2012) English with an accent: Language, ideology, and discrimination in the United States (2nd ed.). London: Routledge. doi:  10.4324/9780203348802
    https://doi.org/10.4324/9780203348802 [Google Scholar]
  44. 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]
  45. 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. doi:  10.1121/1.408177
    https://doi.org/10.1121/1.408177 [Google Scholar]
  46. Mackey, A., & Gass, S.
    (2005) Second language research: Methodology and design. Mahwah, NJ: Lawrence Erlbaum Associates. doi:  10.4324/9781410612564.
    https://doi.org/10.4324/9781410612564 [Google Scholar]
  47. MacWhinney, B.
    (2000) The CHILDES Project: Tools for analyzing talk (3rd ed.). Mahwah, NJ: Lawrence Erlbaum Associates. doi:  10.1177/026565909200800211. Retrieved from childes.talkbank.org/
    https://doi.org/10.1177/026565909200800211 [Google Scholar]
  48. Mixdorff, H., & Ingram, J.
    (2009) Prosodic analysis of foreign-accented English. Proceedings of Interspeech, Brighton, UK.
    [Google Scholar]
  49. 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. InProceedings of the Workshop on Speech and Language Technology in Education (SLaTE), Wroxall Abbey, Warwickshire, UK.
    [Google Scholar]
  50. 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]
  51. 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 llt.msu.edu/vol13num2/motohashisaigohardison.pdf
    [Google Scholar]
  52. Munro, M. J., & Derwing, T. M.
    (2006) The functional load principle in ESL pronunciation instruction: An exploratory study. System, 34, 520–531. doi:  10.1016/j.system.2006.09.004
    https://doi.org/10.1016/j.system.2006.09.004 [Google Scholar]
  53. 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. 10.1515/iral‑2015‑0002
    https://doi.org/10.1515/iral-2015-0002 [Google Scholar]
  54. Murphy, J.
    (1997) Phonology courses offered by MATESOL programs in the US. TESOL Quarterly, 31, 741–764. doi:  10.2307/3587758
    https://doi.org/10.2307/3587758 [Google Scholar]
  55. 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. doi:  10.1076/call.15.5.441.13473
    https://doi.org/10.1076/call.15.5.441.13473 [Google Scholar]
  56. Neumeyer, L., Franco, H., Digalakis, V., & Weintraub, M.
    (2000) Automatic scoring of pronunciation quality. Speech Communication, 30(2), 83–93. 10.1016/S0167‑6393(99)00046‑1
    https://doi.org/10.1016/S0167-6393(99)00046-1 [Google Scholar]
  57. O’Brien, M. G.
    (2011) Teaching and assessing pronunciation with computer technology. InN. 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]
  58. 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 llt.msu.edu/issues/june2016/okunohardison.pdf
    [Google Scholar]
  59. Olson, D. J.
    (2014) Benefits of visual feedback on segmental production in the L2 classroom. Language Learning & Technology, 18(3), 173–192. Retrieved from llt.msu.edu/issues/october2014/olson.pdf
    [Google Scholar]
  60. Pennington, M. C.
    (1999) Computer-aided pronunciation pedagogy: Promise, limitations, directions. Computer Assisted Language Learning, 12(5), 427–440. doi:  10.1076/call.12.5.427.5693
    https://doi.org/10.1076/call.12.5.427.5693 [Google Scholar]
  61. Pennington, M. C., & Ellis, N. C.
    (2000) Cantonese speakers’ memory for English sentences with prosodic cues. The Modern Language Journal, 84(3), 372–389. 10.1111/0026‑7902.00075
    https://doi.org/10.1111/0026-7902.00075 [Google Scholar]
  62. 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]
  63. 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]
  64. Rose, Y., & MacWhinney, B.
    (2014) The PhonBank project: Data and software-assisted methods for the study of phonology and phonological development. InJ. Durand, U. Gut, & G. Kristoffersen (Eds.), The Oxford handbook of corpus phonology (pp. 308–401). Oxford: Oxford University Press.
    [Google Scholar]
  65. 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. doi:  10.1016/j.wocn.2010.11.005
    https://doi.org/10.1016/j.wocn.2010.11.005 [Google Scholar]
  66. Staples, S.
    (2015) Spoken corpora. InD. Biber & R. Reppen (Eds.), The Cambridge handbook of English corpus linguistics (pp. 271–291). Cambridge: Cambridge University Press. 10.1017/CBO9781139764377.016
    https://doi.org/10.1017/CBO9781139764377.016 [Google Scholar]
  67. 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, 6–8June.
    [Google Scholar]
  68. 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]
  69. Strik, H., & Cucchiarini, C.
    (2014) On automatic phonological transcription of speech corpora. InJ. Durand, U. Gut, & G. Kristofferson (Eds.), The Oxford handbook of corpus phonology. Oxford: Oxford University Press. doi:  10.1093/oxfordhb/9780199571932.013.001
    https://doi.org/10.1093/oxfordhb/9780199571932.013.001 [Google Scholar]
  70. Strik, H., Truong, K., de Wet, F., & Cucchiarini, C.
    (2009) Comparing different approaches for automatic pronunciation error detection. Speech Communication, 51(10), 845–852. doi:  10.1016/j.specom.2009.05.007
    https://doi.org/10.1016/j.specom.2009.05.007 [Google Scholar]
  71. Sweet, H.
    (1900) The practical study of languages: A guide for teachers and learners. New York, NY: Henry Holt & Co.
    [Google Scholar]
  72. Thomson, R. I.
    (2011) Computer assisted pronunciation training: Targeting second language vowel perception improves pronunciation. CALICO Journal, 28, 744–765. doi:  10.11139/cj.28.3.744‑765
    https://doi.org/10.11139/cj.28.3.744-765 [Google Scholar]
  73. (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]
  74. (2018) English Accent Coach [Computer program]. Version 2.3. Retrieved from www.englishaccentcoach.com
    [Google Scholar]
  75. Thomson, R. I., & Derwing, T. M.
    (2015) The effectiveness of L2 pronunciation instruction: A narrative review. Applied Linguistics, 36(3), 326–344. doi:  10.1093/applin/amu076
    https://doi.org/10.1093/applin/amu076 [Google Scholar]
  76. (2016) Is phonemic training using nonsense or real words more effective?InJ. 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]
  77. Trouvain, J., & Gut, U.
    (Eds.) (2007) Non-native prosody: Phonetic description and teaching practice. Berlin: Mouton de Gruyter. 10.1515/9783110198751
    https://doi.org/10.1515/9783110198751 [Google Scholar]
  78. 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.
  79. 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. doi:  10.1080/09588221.2016.1167090
    https://doi.org/10.1080/09588221.2016.1167090 [Google Scholar]
  80. 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. doi:  10.1155/2010/973954
    https://doi.org/10.1155/2010/973954 [Google Scholar]
  81. (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. doi:  10.1121/1.4813304
    https://doi.org/10.1121/1.4813304 [Google Scholar]
  82. Weinberger, S. H.
    (2017) Speech Accent Archive. George Mason University. Retrieved from accent.gmu.edu
    [Google Scholar]
  83. Witt, S., & Young, S.
    (2000) Phone-level pronunciation scoring and assessment for interactive language learning. Speech Communication, 30(2/3): 95–108. doi:  10.1016/S0167‑6393(99)00044‑8
    https://doi.org/10.1016/S0167-6393(99)00044-8 [Google Scholar]
  84. Zielinski, B.
    (2008) The listener: No longer the silent partner in reduced intelligibility. System, 36, 69–84. doi:  10.1016/j.system.2007.11.004
    https://doi.org/10.1016/j.system.2007.11.004 [Google Scholar]
http://instance.metastore.ingenta.com/content/journals/10.1075/jslp.17001.obr
Loading
/content/journals/10.1075/jslp.17001.obr
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was successful
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error