根据音高共振峰预测舌头位置，用于语音教学与康复训练
AURORA Model of Formant-to-Tongue Inversion for Didactic and Clinical Applications
- 基于前两个共振峰值推断发音时舌头形状与位移
- 使用40名英语母语者的数据训练，实现语音与舌位的映射
- 提供交互式工具，适合语音学习者与语言治疗师使用
本文介绍了AURORA（声学理解与实时共振发声观测）模型的概念与计算基础。该模型通过前两个共振峰值预测元音发音时的舌头位置与形状，旨在作为语音教学辅助工具，揭示共振峰与发音器官运动的关系，并为生物反馈应用奠定基础。模型基于40名英语母语者的超声舌像与声学数据构建。本文阐述了建模动机、目标及架构，对模型进行了定性评估，聚焦关键舌部特征。此外，开发了两款工具提升可及性：一个Shiny网页应用和一个实时舌位生物反馈原型软件。目标用户包括语音学学生、相关领域语言学家，以及言语治疗师与患者。
原文摘要 · Abstract (English)
This paper outlines the conceptual and computational foundations of the AURORA (Acoustic Understanding and Real-time Observation of Resonant Articulations) model. AURORA predicts tongue displacement and shape in vowel sounds based on the first two formant values. It is intended as a didactic aid helping to explain the relationship between formants and the underlying articulation, as well as a foundation for biofeedback applications. The model is informed by ultrasound tongue imaging and acoustic data from 40 native speakers of English. In this paper we discuss the motivation for the model, the modelling objectives as well as the model architecture. We provide a qualitative evaluation of the model, focusing on selected tongue features. We then present two tools developed to make the model more accessible to a wider audience, a Shiny app and a prototype software for real-time tongue biofeedback. Potential users include students of phonetics, linguists in fields adjacent to phonetics, as well as speech and language therapy practitioners and clients.
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