Abstract
This paper compares the difference in articulation patterns between native (L1) and non-native (L2) Mandarin speakers of English, for the purpose of providing an understanding of mispronunciation behaviors of L2 learners. Consensus transcriptions from the Electromagnetic Articulography Mandarin Accented English (EMA-MAE) corpus are used to identify commonly occurring substitution errors for consonants and vowels. Phoneme level alignments of the utterances produced by speech recognition models are used to extract articulatory feature vectors representing correct and substituted sounds from L1 and L2 speaker groups respectively. The articulatory features that are significantly different between the two groups are identified along with the direction of error for the L2 speaker group. Experimental results provide information about which types of substitutions are most common and which specific articulators are the most significant contributors to those errors.
Original language | English |
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Title of host publication | 2021 IEEE Spoken Language Technology Workshop, SLT 2021 - Proceedings |
Pages | 693-697 |
Number of pages | 5 |
ISBN (Electronic) | 9781728170664 |
DOIs | |
State | Published - Jan 19 2021 |
Event | 2021 IEEE Spoken Language Technology Workshop, SLT 2021 - Virtual, Shenzhen, China Duration: Jan 19 2021 → Jan 22 2021 |
Publication series
Name | 2021 IEEE Spoken Language Technology Workshop, SLT 2021 - Proceedings |
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Conference
Conference | 2021 IEEE Spoken Language Technology Workshop, SLT 2021 |
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Country/Territory | China |
City | Virtual, Shenzhen |
Period | 1/19/21 → 1/22/21 |
Bibliographical note
Publisher Copyright:© 2021 IEEE.
Keywords
- Articulatory features
- Mispronunciation Diagnosis
ASJC Scopus subject areas
- Linguistics and Language
- Language and Linguistics
- Artificial Intelligence
- Computer Science Applications
- Computer Vision and Pattern Recognition
- Hardware and Architecture