@inproceedings{park-etal-2025-compositional,
title = "Compositional Phoneme Approximation for {L}1-Grounded {L}2 Pronunciation Training",
author = "Park, Jisang and
Kim, Minu and
Hong, DaYoung and
Lee, Jongha",
editor = "Inui, Kentaro and
Sakti, Sakriani and
Wang, Haofen and
Wong, Derek F. and
Bhattacharyya, Pushpak and
Banerjee, Biplab and
Ekbal, Asif and
Chakraborty, Tanmoy and
Singh, Dhirendra Pratap",
booktitle = "Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics",
month = dec,
year = "2025",
address = "Mumbai, India",
publisher = "The Asian Federation of Natural Language Processing and The Association for Computational Linguistics",
url = "https://aclanthology.org/2025.ijcnlp-short.35/",
pages = "434--443",
ISBN = "979-8-89176-299-2",
abstract = "Learners of a second language (L2) often map non-native phonemes to similar native-language (L1) phonemes, making conventional L2-focused training slow and effortful. To address this, we propose an L1-grounded pronunciation training method based on compositional phoneme approximation (CPA), a feature-based representation technique that approximates L2 sounds with sequences of L1 phonemes.Evaluations with 20 Korean non-native English speakers show that CPA-based training achieves a 76{\%} in-box formant rate in acoustic analysis, 17.6{\%} relative improvement in phoneme recognition accuracy, and over 80{\%} of speech being rated as more native-like, with minimal training. Project page: \url{https://gsanpark.github.io/CPA-Pronunciation}."
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<abstract>Learners of a second language (L2) often map non-native phonemes to similar native-language (L1) phonemes, making conventional L2-focused training slow and effortful. To address this, we propose an L1-grounded pronunciation training method based on compositional phoneme approximation (CPA), a feature-based representation technique that approximates L2 sounds with sequences of L1 phonemes.Evaluations with 20 Korean non-native English speakers show that CPA-based training achieves a 76% in-box formant rate in acoustic analysis, 17.6% relative improvement in phoneme recognition accuracy, and over 80% of speech being rated as more native-like, with minimal training. Project page: https://gsanpark.github.io/CPA-Pronunciation.</abstract>
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%0 Conference Proceedings
%T Compositional Phoneme Approximation for L1-Grounded L2 Pronunciation Training
%A Park, Jisang
%A Kim, Minu
%A Hong, DaYoung
%A Lee, Jongha
%Y Inui, Kentaro
%Y Sakti, Sakriani
%Y Wang, Haofen
%Y Wong, Derek F.
%Y Bhattacharyya, Pushpak
%Y Banerjee, Biplab
%Y Ekbal, Asif
%Y Chakraborty, Tanmoy
%Y Singh, Dhirendra Pratap
%S Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics
%D 2025
%8 December
%I The Asian Federation of Natural Language Processing and The Association for Computational Linguistics
%C Mumbai, India
%@ 979-8-89176-299-2
%F park-etal-2025-compositional
%X Learners of a second language (L2) often map non-native phonemes to similar native-language (L1) phonemes, making conventional L2-focused training slow and effortful. To address this, we propose an L1-grounded pronunciation training method based on compositional phoneme approximation (CPA), a feature-based representation technique that approximates L2 sounds with sequences of L1 phonemes.Evaluations with 20 Korean non-native English speakers show that CPA-based training achieves a 76% in-box formant rate in acoustic analysis, 17.6% relative improvement in phoneme recognition accuracy, and over 80% of speech being rated as more native-like, with minimal training. Project page: https://gsanpark.github.io/CPA-Pronunciation.
%U https://aclanthology.org/2025.ijcnlp-short.35/
%P 434-443
Markdown (Informal)
[Compositional Phoneme Approximation for L1-Grounded L2 Pronunciation Training](https://aclanthology.org/2025.ijcnlp-short.35/) (Park et al., IJCNLP-AACL 2025)
ACL
- Jisang Park, Minu Kim, DaYoung Hong, and Jongha Lee. 2025. Compositional Phoneme Approximation for L1-Grounded L2 Pronunciation Training. In Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics, pages 434–443, Mumbai, India. The Asian Federation of Natural Language Processing and The Association for Computational Linguistics.