用母语发音模拟目标语言发音，提升二语发音学习效率
Compositional Phoneme Approximation for L1-Grounded L2 Pronunciation Training
- 用母语音素组合逼近第二语言发音，实现跨语言发音映射
- 实验显示语音表征准确率提升17.6%，近80%语音被评更像母语者
- 适合想快速改善发音的二语学习者，尤其韩语母语者学英语
第二语言（L2）学习者常将非母语音素映射到相似的母语（L1）音素，导致传统L2发音训练耗时费力。为此，本文提出基于组合音素近似（CPA）的L1基础发音训练方法，该方法通过特征表示技术，用一系列母语音素序列逼近目标语言发音。对20名韩国非英语母语者的评估表明，该方法在声学分析中达到76%的基频范围匹配率，音素识别准确率相对提升17.6%，超过80%的语音被评价为更接近母语发音，且仅需少量训练即可实现。
原文摘要 · Abstract (English)
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.
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