Cover not available

Article published In: International Journal of Learner Corpus Research
Vol. 8:2 (2022) ► pp.190–236

Get fulltext from our e-platform
JBE logo with link
PDF logo with download linkDownload PDF
EPUB logo with download linkDownload EPUB
authorization required

Integrating fluency and prosody into multidimensional analysis

Exploring the multidimensional nature of spoken learner language

 | University of Arizona
 | Ruhr University Bochum
Published online: 26 January 2023
DOI logo with link
https://doi.org/10.1075/ijlcr.21012.sta
Abstract
Investigation of the characteristics of spoken learner language has increased in recent years but has been primarily limited to the investigation of one linguistic level (e.g., lexico-grammar), which gives a limited picture of learners’ overall linguistic competence (e.g., Skarnitzl, R., & Rumlová, J. (2019). Phonetic aspects of strongly-accented Czech speakers of English. Acta Universitatis Carolinae: Philologica / Phonetica Pragensia, 21, 109–128. Google Scholar logo with link to Google Scholar). In this study, we investigate lexico-grammar, fluency, and prosody in LINDSEI (German, Czech, and Spanish) alongside British and American English comparable corpora, using multidimensional analysis, a statistical procedure that identifies co-occurring linguistic features and leads to functional interpretation of the discourse. Results show significant differences between L1 and L2 groups on four of six dimensions and reveal novel patterns of co-occurrence. Dimension 1, for example, identifies correlates of informationally driven discourse on all three linguistic levels under investigation. These findings show the importance of including multiple linguistic levels in the analysis of learner discourse and have implications for a more holistic and functionally based approach to language instruction.
Article outline
  • 1.Introduction
  • 2.Literature review
    • 2.1Previous learner corpus research on lexico-grammar, fluency, or prosody
    • 2.2Relationships among linguistic levels in L2 speech
  • 3.Methods
    • 3.1Corpora
    • 3.2Multidimensional Analysis
    • 3.3Functional interpretation
    • 3.4Investigation of the dimensions across language background
  • 4.Results
    • 4.1Overview
    • 4.2Dimension 1
    • 4.3Dimension 3
    • 4.4Dimension 4
    • 4.5Dimension 5
  • 5.Discussion
  • 6.Limitations
  • 7.Conclusion
  • Notes
  • References
References (56)
References
Aguado-Jiménez, P., Pérez-Paredes, P., & Sánchez, P. (2012). Exploring the use of multidimensional analysis of learner language to promote register awareness. System, 40(1), 90–103. Google Scholar logo with link to Google Scholar
Algeo, J. (2010). The origins and development of the English language. Cengage Learning.Google Scholar logo with link to Google Scholar
Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67(1), 1–48. Google Scholar logo with link to Google Scholar
Beckman, M. E., & Pierrehumbert, J. (1986). Intonational structure in Japanese and English. Phonology Yearbook, 31, 255–309. Google Scholar logo with link to Google Scholar
Biber, D. (1988). Variation across speech and writing. Cambridge University Press. Google Scholar logo with link to Google Scholar
Biber, D. & Gray, B. (2013). Discourse characteristics of writing and speaking task types on the TOEFL iBT (TOEFL iBT Research Report No. 19). Educational Testing Service.Google Scholar logo with link to Google Scholar
Biber, D., & Staples, S. (2014). Exploring the prosody of stance. In T. Raso & H. Mello (Eds.), Spoken corpora and linguistic studies (pp. 271–294). John Benjamins. Google Scholar logo with link to Google Scholar
Biber, D., Gray, B., & Staples, S. (2016). Predicting patterns of grammatical complexity across language exam task types and proficiency levels. Applied Linguistics, 37(5), 639–668. Google Scholar logo with link to Google Scholar
Biber, D., Johansson, S., Leech, G., Conrad, & Finegan, E. (2021). Grammar of Spoken and Written English. John Benjamins. Google Scholar logo with link to Google Scholar
Bigi, B. (2015). SPPAS - Multilingual Approaches to the Automatic Annotation of Speech. The Phonetician, 111-1121: 55-69.Google Scholar logo with link to Google Scholar
Boersma, P., & Weenink, D. (2019). Praat: doing phonetics by computer (Version 6.0.43) [Computer software]. [URL]
Brazil, D. (1997). The communicative value of intonation in English. Cambridge University Press.Google Scholar logo with link to Google Scholar
Chamonikolasová, J. (2017). Intonation in English and Czech dialogues. Masarykova univerzita.Google Scholar logo with link to Google Scholar
Clopper, C. G., & Pisoni, D. B. (2006). The Nationwide Speech Project: A new corpus of American English dialects. Speech Communication, 481, 633–644. Google Scholar logo with link to Google Scholar
Dallaston, K. & Docherty, G. (2020). The quantitative prevalence of creaky voice (vocal fry) in varieties of English: A systematic review of the literature. PLoS ONE, 15(3), e0229960. Google Scholar logo with link to Google Scholar
De Cock, S. (2004). Preferred sequences of words in NS and NNS speech. Belgian Journal of English Language and Literatures (BELL), New Series 21, 225–246.Google Scholar logo with link to Google Scholar
De Jong, N.H., Pacilly, J., & Heeren, W. (2021). PRAAT scripts to measure speed fluency and breakdown fluency in speech automatically. Assessment in Education: Principles, Policy & Practice, 28(4), 456-476. Google Scholar logo with link to Google Scholar
Egbert, J. & Staples, S. (2019). Doing multi-dimensional analysis in SPSS, SAS, and R. In T. Berber-Sardinha & M. Veirano-Pinto (Eds.), Multi-dimensional analysis research methods and current issues (pp. 124–144). Bloomsbury. Google Scholar logo with link to Google Scholar
Ellis, N. (2008). The dynamics of second language emergence: Cycles of language use, language change, and language acquisition. Modern Language Journal, 921, 232–249. Google Scholar logo with link to Google Scholar
Fuchs, R., Götz, S., & Werner, V. (2016). The present perfect in learner Englishes: A corpus-based case study on L1 German intermediate and advanced speech and writing. In V. Werner, E. Seoane, & C. Suárez-Gómez (Eds.), Re-Assessing the present perfect (pp. 297–338). Mouton de Gruyter. Google Scholar logo with link to Google Scholar
García Lecumberri, M. L., Cooke, M., & Wester, M. (2017). A bi-directional task-based corpus of learners’ conversational speech. International Journal of Learner Corpus Research, 4(2), 175–195. Google Scholar logo with link to Google Scholar
Gilquin, G. (2018). Exploring the spoken learner English construction: A corpus-driven approach. In R. Alonso (Ed.), Speaking in a Second Language (pp. 127–152). John Benjamins. Google Scholar logo with link to Google Scholar
Gilquin, G., De Cock, S., & Granger, S. (Eds.). (2010). Louvain International Database of Spoken English Interlanguage (LINDSEI). Presses universitaires de Louvain.Google Scholar logo with link to Google Scholar
Goldman, J.-P. (2011). EasyAlign: an automatic phonetic alignment tool under Praat. In P. Cosi, R. De Mori, G. Di Fabbrizio, & R. Pieraccini (Eds.). Proceedings of 12th Annual Conference of the International Speech Communication Association (INTERSPEECH), 3233-3236. Firenze, Italy.Google Scholar logo with link to Google Scholar
Gráf, T. (2015). Accuracy and fluency in the speech of the advanced learner of English (Unpublished doctoral dissertation). Charles University.
Gut, U. (2009). Non-native speech: A corpus-based analysis of phonological and phonetic properties of L2 English and German. Peter Lang. Google Scholar logo with link to Google Scholar
Gutiérrez Díez, F. (2012). Trouble spots in the learning of English intonation by Spanish speakers: Tonality and tonicity. In J. Romero-Trillo (Ed.), Pragmatics and prosody in English language teaching (pp. 219–230). Springer. Google Scholar logo with link to Google Scholar
Heldner, M., Włodarczak, M., Beňuš, Š., & Gravano, A. (2019, September). Voice quality as a turn-taking cue. Paper presented at the Interspeech 2019, Graz, Austria.
Huang, L.-F., Kubelec, S., Keng, N., & Hsu, L.-H. (2018). Evaluating CEFR rater performance through the analysis of spoken learner corpora. Language Testing in Asia, 8 (14). 1–17. Google Scholar logo with link to Google Scholar
J. Murrey Atkins Library (2019). New South Voices Collection [Online repository]. The University of North Carolina at Charlotte.Google Scholar logo with link to Google Scholar
Kang, O. (2013). Linguistic analysis of speaking features distinguishing general English exams at CEFR levels B1 to C2 and examinee L1 backgrounds. Research Notes, 521, 40–48.Google Scholar logo with link to Google Scholar
Kang, O., & Yan, X. (2018). Linguistic features distinguishing examinees’ speaking performances at different proficiency levels. Journal of Language Testing and Assessment, 11, 24–39. Google Scholar logo with link to Google Scholar
Klein, W., & Perdue, C. (1997). The basic variety (or: Couldn’t natural languages be much simpler?). Second Language Research, 131, 301–347. Google Scholar logo with link to Google Scholar
LaFlair, G., & Staples, S. (2017). Using corpus linguistics to examine the extrapolation inference in the validity argument for a high-stakes speaking assessment. Language Testing 34(4): 451–475. Google Scholar logo with link to Google Scholar
LaFlair, G., Staples, S., & Egbert, J. (2015). Variability in the MELAB speaking task: Investigating linguistic characteristics of test-taker performances in relation to rater severity and score (CaMLA Working Papers 2015–04). [URL]
LaFlair, G., Staples, S., & Yan, X. (2019). Triangulating corpus linguistics and language assessment: Using corpus linguistics to enhance validity arguments. In P. Baker & J. Egbert (Eds.), Using corpus methods to triangulate linguistic analysis (pp. 109–140). Routledge. Google Scholar logo with link to Google Scholar
Lin, P. (2018). The prosody of formulaic sequences: A corpus and discourse approach. Continuum.Google Scholar logo with link to Google Scholar
Munro, M., & Derwing, T. (2001). Modelling perceptions of the accentedness and comprehensibility of L2 speech: The role of speaking rate. Studies in Second Language Acquisition, 23(4), 451–468. Google Scholar logo with link to Google Scholar
Pérez-Paredes, P., & Sánchez Tornel, M. (2015). A multidimensional analysis of learner language during story reconstruction in interviews. In M. Callies & S. Götz (Eds.), Learner Corpora in Language Testing and Assessment (pp. 141–162). John Benjamins. Google Scholar logo with link to Google Scholar
Picoral, A., Staples, S., & Reppen, R. (2021). Automated annotation of learner English: An evaluation of software tools. International Journal of Learner Corpus Research, 7(1), 17–52. Google Scholar logo with link to Google Scholar
Puga, K. (2021). English intonation of advanced learners: A contrastive interlanguage analysis (Unpublished doctoral dissertation). Justus Liebig University Gießen.
Ramírez-Verdugo, M. D. (2022). Intonation in L2 discourse: Research insights. Routledge.Google Scholar logo with link to Google Scholar
Redi, L. & Shattuck-Hufnagel, S. (2001). Variation in the realization of glottalization in normal speakers. Journal of Phonetics, 29(4), 407–429. Google Scholar logo with link to Google Scholar
Romero-Trillo, J. (2019). Prosodic pragmatics and feedback in intercultural communication. S. Götz & J. Mukherjee (Eds.), Learner Corpora and Language Teaching (pp. 191–217). John Benjamins. Google Scholar logo with link to Google Scholar
Silverman, K., Beckman, M., Pitrelli, J., Ostendorf, M., Wightman, C., Price, P., Pierrehumbert, J., & Hirschberg, J. (1992). ToBI: A standard scheme for labeling prosody. Proceedings of the 2nd International Conference on Spoken Language Processing 1992, 867–870.Google Scholar logo with link to Google Scholar
Skarnitzl, R., & Rumlová, J. (2019). Phonetic aspects of strongly-accented Czech speakers of English. Acta Universitatis Carolinae: Philologica / Phonetica Pragensia, 21, 109–128. Google Scholar logo with link to Google Scholar
Van Rooy, B., & Terblanche, L. (2009). A multi-dimensional analysis of a learner corpus. In A. Renouf & A. Kehoe (Eds.), Corpus Linguistics (pp. 239–254). Brill Rodopi. Google Scholar logo with link to Google Scholar
Volín, J., Poesová, K., & Weingartová, L. (2015). Speech melody properties in English, Czech and Czech English: Reference and interference. Research in Language, 13(1), 107–123. Google Scholar logo with link to Google Scholar
Wennerstrom, A., & Siegel, A. F. (2003). Keeping the floor in multiparty conversations: Intonation, syntax, and pause. Discourse Processes, 361, 77–107. Google Scholar logo with link to Google Scholar
Wolk, C., Götz, S., & Jäschke, K. (2020). Possibilities and drawbacks of using an online application for semi-automatic corpus analysis to investigate discourse markers and alternative fluency variables. Corpus Pragmatics, 51, 7–36. Google Scholar logo with link to Google Scholar
Yan, X., Kim, H., & Kim, J. (2020). Dimensionality of speech fluency: Examining the relationships among complexity, accuracy, and fluency (CAF) features of speaking performances on the Aptis test. Language Testing, 38(4), 1–26.Google Scholar logo with link to Google Scholar
Zimmerer, F., Jügler, J., Andreeva, B., Möbius, B., & Trouvain, J. (2014). Too cautious to vary more? A comparison of pitch variation in native and non-native productions of French and German speakers. Proceedings of Speech Prosody, 71, 1037–1041. Google Scholar logo with link to Google Scholar
Cited by (1)

Cited by one other publication

This list is based on CrossRef data as of 12 december 2025. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.

Mobile Menu Logo with link to supplementary files background Layer 1 prag Twitter_Logo_Blue