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

语调音系层次理论中音调对齐的全局测量人类语言以各种令人眼花缭乱的方式使用音高来传达意义。在所有语言中，音高（作为言语韵律的一个方面）都可以表达态度或情感。在一些语言中，比如英语，音高模式，通常被称为语调轮廓，也表达了区别，比如疑问和陈述句之间的区别。另一方面，在像普通话这样的语言中，被称为音调的音高模式进一步表明了单词之间的差异，而这些单词本来是相同的。尽管近几十年来取得了重大进展，但语调和语调这一语言现象的统一理论解释在关键方面仍然难以捉摸。事实上，甚至在如何最好地表征像英语这样的语言的语调轮廓的形式属性方面，仍然没有普遍的共识。似乎缺少的是一个共同的声学或发音词汇来表达相关的区别，一个单一的可测量的维度，在这个维度内，无论研究的语言是什么，轮廓都可以可靠地区分出来。本项目开发了一种新的数学方法，基于音调重心的概念，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，并将在两种实验中测试我们的模型的适用性。第一种方法是在实验环境中对母语人士录制的音高轮廓进行自动分类。第二种方法是通过语音合成音调轮廓的一些物理特征来直接操纵，这些特征可能与传达说话者的意图有关，看看哪些变量对听者对话语意义的判断影响最大。该项目为人类语言中音调对比的产生和感知的统一方法奠定了基础，一种表达系统差异的方法，同时捕捉语言之间更深层次的共性。这项工作的结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感知相关特征将使语音合成系统更加真实。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为第二语言学习者提供更多有用的反馈。最后，该模型将有助于语音理解系统的语调轮廓自动分类。这一领域的进展最终将使这种系统不仅可以从话语中的单词序列中获得意义，还可以从语调所传达的细微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.