TarDiS: Targets and Dynamics in Speech

TarDiS：语音中的目标和动态

基本信息

批准号：
AH/S011900/1
负责人：
Patrycja Strycharczuk
金额：
$ 25.9万
依托单位：
University of Manchester
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2019
资助国家：
英国
起止时间：
2019 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=AH%2FS011900%2F1
关键词：
TarDiS Targets Dynamics Speech

项目摘要

Speech is a physical phenomenon: it can be represented as a series of vocal tract movements, or as sound waves. However, in order for speech to serve a communicative function, it also must include more abstract components, building blocks that pair these physical phenomena with linguistic meaning. For instance, the vowel /ai/ in a word like 'kite', can be represented in multiple ways. Physiologically, it involves tongue movement from a lower and more far back position to the high front corner of the mouth, but at the same time /ai/ is an abstract category, a family of sounds brought together by their joint meaningful function. The vowel /ai/ is a contrastive unit in English, one that makes words like 'kite' different from words like 'kit'. Most native speakers of English never need to ponder the nature of the category /ai/, yet they somehow acquire a systematic mapping that links the physical form of /ai/ with its meaning. To linguists, understanding this process holds the key to understanding how language works. It is by this type of mapping that a movement of the tongue acquires linguistic meaning. This research project sets out to probe the nature of vowel categories like /ai/, and more specifically what their abstract representations must contain in order to successfully model variation observed in speech. This is an old problem in speech science, which we intend to approach using a novel type of data: combination of computational modelling, measurements of tongue movement based on tracking such movement in a magnetic field, and images of tongue acquired with ultrasound, as well as the audio signal. We will record such data from twenty native speakers from a single speech community (West Yorkshire) pronouncing all vowels in their variety of English. We will then consider various abstract features that we can derive from the physical signal, and the minimum number of such features needed to successfully capture all vowel categories. For instance, we want to know whether vowels such as /ai/ are best modelled as consisting of one or two elements, and how much information about movement we need to encode in order to successfully model /ai/ within a vowel system.We will extend the implications of our findings to practical applications. Although vowel categories and vowel targets do not feature overtly in natural acquisition of language, they become important in situations where explicit speech instruction plays a role, such as speech therapy. The more we understand about the nature of speech sounds, the more successful we can be in teaching them. Therefore, we will present our findings on speech goals from a theoretical modelling perspective to clinical speech researchers and clinical practitioners, and engage them in a discussion of how such abstract speech targets can be used as tools in speech therapy.

语音是一种物理现象：它可以表示为一系列声道运动或声波。然而，为了使语音发挥交流功能，它还必须包括更抽象的成分，将这些物理现象与语言意义配对的构建块。例如，像“kite”这样的单词中的元音/ai/可以用多种方式表示。从生理学上讲，它涉及舌头从较低且较远的后部位置到嘴部较高的前角的运动，但同时 /ai/ 是一个抽象类别，是由其联合有意义的功能聚集在一起的一系列声音。元音 /ai/ 是英语中的一个对比单位，它使“kite”等单词与“kit”等单词不同。大多数以英语为母语的人从来不需要思考 /ai/ 类别的本质，但他们以某种方式获得了将 /ai/ 的物理形式与其含义联系起来的系统映射。对于语言学家来说，理解这个过程是理解语言如何运作的关键。正是通过这种类型的映射，舌头的运动才获得了语言意义。该研究项目旨在探讨 /ai/ 等元音类别的本质，更具体地说，为了成功地对语音中观察到的变化进行建模，它们的抽象表示必须包含哪些内容。这是语音科学中的一个老问题，我们打算使用一种新型数据来解决这个问题：计算模型、基于跟踪磁场中舌头运动的舌头运动测量以及通过超声波获取的舌头图像的组合作为音频信号。我们将记录来自同一语音社区（西约克郡）的二十位母语人士的此类数据，他们用各种英语发音所有元音。然后，我们将考虑可以从物理信号中导出的各种抽象特征，以及成功捕获所有元音类别所需的此类特征的最小数量。例如，我们想知道像 /ai/ 这样的元音是否最好建模为由一个或两个元素组成，以及我们需要编码多少有关运动的信息才能在元音系统中成功建模 /ai/。我们将将我们的发现的影响扩展到实际应用。尽管元音类别和元音目标在语言的自然习得中并不明显，但在明确的言语指导发挥作用的情况下（例如言语治疗），它们变得很重要。我们对语音的本质了解得越多，我们在教授语音方面就越成功。因此，我们将从理论建模的角度向临床言语研究人员和临床实践者展示我们关于言语目标的发现，并让他们参与讨论如何将这种抽象的言语目标用作言语治疗的工具。