分析英语口音对语音的影响，发现非母语者发音更简单、音调更高。
Analyzing the Impact of Accent on English Speech: Acoustic and Articulatory Perspectives
- 从发音和声学角度分析口音，用特征向量量化口音强度。
- 非母语者口音平均音调更高，发音协调模式更简单。
- 无需繁琐语音转录，适合开发包容性语音系统。
AI语音应用在医疗、客服等领域快速发展，但全球交流中非母语口音日益普遍，而现有系统多基于母语数据训练，难以应对。本研究通过发音机制与声学分析，发现非母语英语口音具有更简单的发音协调模式和更高的平均音调。利用特征谱（eigenspectra）与声道变量协调特征，提出一种无需依赖资源密集型语音转录的口音强度量化方法。研究为理解口音对语音可懂度的影响提供新视角，并有助于构建更包容、鲁棒的语音处理系统，支持多元语言群体。
原文摘要 · Abstract (English)
Advancements in AI-driven speech-based applications have transformed diverse industries ranging from healthcare to customer service. However, the increasing prevalence of non-native accented speech in global interactions poses significant challenges for speech-processing systems, which are often trained on datasets dominated by native speech. This study investigates accented English speech through articulatory and acoustic analysis, identifying simpler coordination patterns and higher average pitch than native speech. Using eigenspectra and Vocal Tract Variable-based coordination features, we establish an efficient method for quantifying accent strength without relying on resource-intensive phonetic transcriptions. Our findings provide a new avenue for research on the impacts of accents on speech intelligibility and offer insights for developing inclusive, robust speech processing systems that accommodate diverse linguistic communities.
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