The pitch contours of Mandarin two-character words are generally understood as being shaped by the underlying tones of the constituent single-character words, in interaction with articulatory constraints imposed by factors such as speech rate, co-articulation with adjacent tones, segmental make-up, and predictability. This study shows that tonal realization is also partially determined by words' meanings. We first show, on the basis of a Taiwan corpus of spontaneous conversations, using the generalized additive regression model, and focusing on the rise-fall tone pattern, that after controlling for effects of speaker and context, word type is a stronger predictor of pitch realization than all the previously established word-form related predictors combined. Importantly, the addition of information about meaning in context improves prediction accuracy even further. We then proceed to show, using computational modeling with context-specific word embeddings, that token-specific pitch contours predict word type with 50% accuracy on held-out data, and that context-sensitive, token-specific embeddings can predict the shape of pitch contours with 30% accuracy. These accuracies, which are an order of magnitude above chance level, suggest that the relation between words' pitch contours and their meanings are sufficiently strong to be functional for language users. The theoretical implications of these empirical findings are discussed.

翻译：双音节词的音高轮廓通常被认为由构成词的单音节字的底层层调决定，并受到语速、相邻声调协同发音、音段构成及可预测性等因素带来的发音限制影响。本研究揭示声调实现也部分受词语含义决定。我们首先基于台湾自发性对话语料库，采用广义加性回归模型聚焦升降调模式，发现控制说话人与语境效应后，词类对音高实现的预测力超过所有先前确立的词语形式相关预测因子总和。更重要的是，在语境中加入含义信息可进一步提升预测精度。继而通过结合语境特定词嵌入的计算建模，我们发现：在保留数据中，词元特定音高轮廓预测词类的准确率达50%；而上下文敏感的元特定嵌入预测音高轮廓形状的准确率达30%。这些比随机水平高一个数量级的准确率表明，词语音高轮廓与其含义之间的关系足够显著，可对语言使用者产生功能效用。本文还讨论了这些实证发现的理论意义。