词语意义影响普通话元音的发音细节，研究发现语义可预测元音轨迹。
Word meaning co-determines vowel-inherent spectral change. A corpus-based investigation of conversational Mandarin
- 用语境化词嵌入建模元音动态变化
- 语义信息能显著提升元音轨迹预测准确率
- 适合研究语音与语义关系的学者参考
本研究基于自然对话数据，探究普通话中元音固有频谱变化（VISC）现象。通过广义加性模型与分布语义词嵌入，控制元音时长、性别、说话人身份、共构音、元音类型及句内位置等变量后发现，元音共振峰轨迹具有词特异性成分，且其动态变化可由语境化词嵌入预测，预测精度显著高于置换基线。该结果挑战了言语产生的模块化认知模型，表明词语语义会共同决定其发音的精细特征。
原文摘要 · Abstract (English)
This study investigates vowel-inherent spectral change (VISC) in spontaneous conversational Mandarin. Using the generalized additive model and word embeddings from distributional semantics, we show that, when controlling for variables such as vowel duration, gender, speaker identity, co-articulation, vowel identity, and utterance position, vowel formant trajectory dynamics have word-specific components that are tied to their meaning in context: The F1 and F2 trajectories of words can be predicted from their contextualized embeddings with an accuracy that substantially exceeds a permutation baseline. Challenging modular cognitive models of speech production, these results indicate that, words' semantics co-determine the fine details of their articulation.
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