Collaborative Research: Global Measures of Tonal Alignment in a Level-based Theory of Intonational Phonology

语调层次理论中声调对齐的全球测量人类语言使用音高以令人困惑的各种方式来传达意思。在所有语言中，音调(作为言语韵律的一个方面)可以表达态度或情感。在一些语言中，如英语，音调模式，通常称为语调轮廓，也表达了诸如疑问句和陈述句之间的区别。另一方面，在普通话等语言中，被称为声调的音调模式更进一步地表明了在其他方面相同的单词之间的差异。尽管近几十年来取得了重大进展，但对于被称为语调和语调的语言现象，在关键方面仍然缺乏统一的理论解释。事实上，甚至在如何最好地描述像英语这样的语言中语调轮廓的形式特征方面，仍然没有普遍的共识。似乎缺少一个表达相关区别的通用声学或发音词汇，即一个单一的可测量的维度，在这个维度内，无论使用何种语言，都可以可靠地区分轮廓。这个项目开发了一种新的数学方法，基于声调重心的概念来表征英语中的音高差异。这种方法调和了实验文献中关于对比音高轮廓感知的看似矛盾的结果。我们的研究将集中在少量的英语语调轮廓上，并将在两个实验中测试我们的模型的适用性。第一个涉及在实验环境中对来自本族语的人记录的基音轮廓进行自动分类。第二种是通过语音合成可能涉及说话人意图的音调轮廓的一些物理特征来直接操纵，以确定哪些变量对听话者对话语意义的判断影响最大。该项目为人类语言中声调对比的产生和感知奠定了基础，这种方法表达了系统的差异，同时捕捉了语言之间更深层次的共性。这项工作的成果也将在语音技术领域产生更广泛的影响。例如，识别不同语调模式的知觉相关特征将使语音合成系统更具真实感。此外，能够自动区分相似但感知上不同的轮廓将允许自动发音训练系统给第二语言学习者提供更有帮助的反馈。最后，这种新的模型将有助于语音理解系统中语调轮廓的自动分类。这一领域的进步最终将使这类系统不仅从话语中的单词序列中获得意义，而且还从语调传达的微妙意义差异中获得意义。

Global Measures of Tonal Alignment in a Level-based Theory of Intonational PhonologyHuman languages use pitch to convey meaning in a bewildering variety of ways. In all languages, pitch (as one aspect of speech prosody) can express attitude or emotion. In some languages, like English, pitch patterns, usually called intonation contours, also express distinctions such as that between a question and a statement. In languages like Mandarin Chinese, on the other hand, pitch patterns called tones go still further to signal differences between words that are otherwise identical. Despite significant advances in recent decades, a unified theoretical account of the linguistic phenomena called tone and intonation remains elusive in crucial respects. In fact, there is still no universal agreement even over how best to characterize the formal properties of intonation contours in languages like English. What seems to be missing is a common acoustic or articulatory vocabulary for the expression of the relevant distinctions, a single measurable dimension within which contours can be reliably distinguished regardless of the language under investigation. This project develops a new mathematical approach, based on the notion of Tonal Center of Gravity, to characterizing pitch distinctions in English. This approach reconciles seemingly contradictory results from the experimental literature on the perception of contrasting pitch contours. Our research will concentrate on a small number of intonation contours from English, and will test the applicability of our model in two kinds of experiments. The first involves automatic classification of pitch contours recorded from native speakers in an experimental setting. The second involves direct manipulation through speech synthesis of a number of the physical characteristics of pitch contours that might be involved in conveying speakers' intentions, to see which variables have the greatest effect on listeners' judgments of utterance meaning.The project lays the groundwork for a unified approach to the production and perception of tonal contrasts in human language, one that expresses how systems differ, while capturing the deeper commonality among languages at the same time. The results of this work will also have a broader impact in the area of speech technology. For example, identifying the perceptually relevant characteristics of distinct intonation patterns will allow for greater realism in speech synthesis systems. In addition, being able to distinguish automatically between similar but perceptually distinct contours will allow automatic pronunciation training systems to give more helpful feedback to second language learners. Finally, this new model will facilitate automatic categorization of intonation contours for speech understanding systems. Progress in this area will ultimately allow such systems to derive meaning not just from the sequence of words in an utterance, but from the subtle meaning differences conveyed by intonation as well.