Designing and implementing a corpus-based online pronunciation learning platform for Cantonese learners of Mandarin

Chen, Hsueh Chu; Han, Qian Wen

doi:10.1080/10494820.2018.1510422

Cited by 6 publications

(5 citation statements)

References 12 publications

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“…Four studies to date have investigated the use of audio corpora for L2 pronunciation skills (Chen & Han, 2020;Fu & Yang, 2019;Kartal & Korucu-Kis, 2020;Sardegna & Jarosz, 2022), all of which found positive outcomes. Three of these studies used the same corpus tool for DDLfP: YouGlish, an online concordancer for YouTube.…”

Section: Data-driven Learning and Spoken Discoursementioning

confidence: 99%

“…Other comparisons in their study did not find significant differences in pre/post comparisons, but the study's power (n = 12) is likely to inhibit statistical significance and the generalizability of the findings. Only one of these studies investigated languages other than English, providing preliminary indications through interviews and learner selfassessment that DDLfP was effective for L1 Cantonese learners of Mandarin (Chen & Han, 2020). Accordingly, the current study seeks to employ audio to bring an additional dimension to efforts to incorporate data into learning speaking skills, and more specifically, pronunciation.…”

Section: Data-driven Learning and Spoken Discoursementioning

confidence: 99%

“…The intersection of Data-Driven Learning and L2 pronunciation has only begun to receive attention but a focus on the academic context as well as intelligibility through highly proficient L2 speaker models has yet to be fully explored. While previous research has established the usefulness of DDLfP in general (Chen & Han, 2020;Fu & Yang, 2019;Kartal & Korucu-Kis, 2020), as well as lexical stress (Sardegna & Jarosz, 2022), much is yet unknown regarding the use, effect, and perceptions of DDLfP for prominence in multi-word units and how it may compare to more traditional teacher-generated instruction, including measures of both perception and production skills. To this end, this study is guided by the following three research questions:…”

Section: The Present Studymentioning

confidence: 99%

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Data‐Driven Learning for Pronunciation: Perception and Production of Lexical Stress and Prominence in Academic English

Hirschi,

Kang

2024

TESOL Quarterly

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Issues of intelligibility may arise amongst English learners when acquiring new words and phrases in North American academic settings, perhaps in part due to limited linguistic data available to the learner for understanding language use patterns. To this end, this paper examines the effects of Data‐Driven Learning for Pronunciation (DDLfP) on lexical stress and prominence in the US academic context. 65 L2 English learners in North American universities completed a diagnostic and pretest with listening and speaking items before completing four online lessons and a posttest on academic words and formulas (i.e., multi‐word sequences). Experimental group participants (n = 40) practiced using an audio corpus of highly proficient L2 speakers while comparison group participants (n = 25) were given teacher‐created pronunciation materials. Logistic regression results indicated that the group who used the corpus significantly increased their recognition of prominence in academic formulas. In the spoken tasks, both groups improved in their lexical stress pronunciation, but only the DDLfP learners improved their production of prominence in academic formulas. Learners reported that they valued DDLfP efforts for pronunciation learning across contexts and speakers. Findings have implications for teachers of L2 pronunciation and support the use of corpora for language teaching and learning.

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Section: Data-driven Learning and Spoken Discoursementioning

confidence: 99%

Section: Data-driven Learning and Spoken Discoursementioning

confidence: 99%

Section: The Present Studymentioning

confidence: 99%

See 1 more Smart Citation

Data‐Driven Learning for Pronunciation: Perception and Production of Lexical Stress and Prominence in Academic English

Hirschi,

Kang

2024

TESOL Quarterly

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“…It has been suggested by many previous studies that it is of great value to analyse learner corpora as these can provide opportunities to discover the typical patterns of a certain language used by learners from real language data (e.g., Kettemann & Marko, 2002;Chen & Wang, 2016). By observing the patterns of speech data, we can spot the common features learners typically and most frequently display, which will be pedagogically helpful for students to "become aware of the features of their own inter-language and possibly stimulate a restructuring of their own language use and knowledge" (Gut, 2005, p. 1).…”

Section: Learner Corpora and Language Learningmentioning

confidence: 99%

Linguistic Feature Analyses of Chinese Learners of English and Contributions of Discrete Features to Perceptual Judgment

Chen¹

2018

ELT

Self Cite

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This study (a) conducted a feature analysis of the spoken data of Chinese university students in pronunciation, grammar, and discourse, (b) investigated the contributions of the discrete linguistic features to the perceptual ratings on foreign accent, comprehensibility, delivery, and general language use. Ten university learners were selected from the Spoken Corpus of the English of Hong Kong and Mainland Chinese learners (http://corpus.ied.edu.hk/phonetics/), in which two speakers were paired up to conduct a five minutes interview. Three-level analyses were done to investigate Chinese learners’ linguistic features. Forty listeners from four L1 language backgrounds were recruited to rate the speech samples. The results show that strongly negative correlations were found between the production and perceptual rating scores for “omission of consonant(s) in final position” “redundant article ‘the’”, “silent pauses” and “discourse markers,” suggesting that the four features can be perceived and exert strong negative influences on perceptual judgments. Pronunciation rating had the strongest positive correlations with “foreign accentedness”; grammar rating had the strongest positive correlations with “general language use”; discourse rating had the strongest positive correlations with “general delivery”, and “general language use.” Regarding the rating of comprehensibility, “misuse of conjunctions” “redundant article ‘the’”, “silent pauses”, “lengthening”, and “stressing” showed strong negative correlations whereas “filled pauses” had strong positive correlations with it. Regarding the rating of foreign accentedness, strong negative correlations were found between “omission of consonant(s) in final position”, “lengthening”, “discourse markers”, and “stressing” and the rating of “foreign accentedness”.

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“…Furthermore, English pronunciation contains many complex details, making it difficult for Indonesian students to adequately acquire the indicators of English pronunciation. Segmental and suprasegmental sounds are used in English pronunciation (Chen & Han, 2018). Vowel sounds, consonant sounds, and sound combinations are all covered by segmental sounds.…”

Section: Introductionmentioning

confidence: 99%

Improving Students’ English Pronunciation Competence by Using Shadowing Technique

Utami

Morganna

2022

Engl. Franca acad. j. of Engl. lang. and educ.

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This study used classroom action research at SMPN 1 Curup Timur in Bengkulu, using the shadowing technique to assist students in resolving their English pronunciation issues. As participants, 25 ninth-grade students were involved. The shadowing technique was carried out in two cycles, with each cycle consisting of three meetings. Two meetings were scheduled for the shadowing learning processes, with the third serving as a post-test. Observations and tests were used to collect data. The data were analyzed both qualitatively and quantitatively. This study uncovered two sets of data. First, for each meeting in each cycle, the process of learning English pronunciation using shadowing techniques included ten stages that included listening, listening while marking, mumbling, parallel reading, comprehending meanings, shadowing prosody sounds, recording, listening, and making comparisons, reviewing, and reflecting. Second, the shadowing technique was effective in improving students' English pronunciation skills. In cycle one, this technique was capable of improving English pronunciation indicators such as phonemes, sound combinations, and sound linkage. Following that, in cycle two, this technique could improve four other indicators: allophones, stress, rhythm and pitch, and intonation.

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Designing and implementing a corpus-based online pronunciation learning platform for Cantonese learners of Mandarin

Cited by 6 publications

References 12 publications

Data‐Driven Learning for Pronunciation: Perception and Production of Lexical Stress and Prominence in Academic English

Data‐Driven Learning for Pronunciation: Perception and Production of Lexical Stress and Prominence in Academic English

Linguistic Feature Analyses of Chinese Learners of English and Contributions of Discrete Features to Perceptual Judgment

Improving Students’ English Pronunciation Competence by Using Shadowing Technique

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