arXiv:2507.03149eess.AScs.AI2025-07中稿 · Interspeech2025被引 2

通过声学特征推断发音差异,量化美英英语口音强弱关系

On the Relationship between Accent Strength and Articulatory Features

  • 用音素级差异衡量口音强度,结合自监督发音反演技术估计发音特征
  • 发现美式与英式英语在卷舌音和后低元音上存在显著发音位置差异
  • 适用于语音处理中的口音分析与发音建模,尤其适合多语言语音系统

本文研究声学语音中口音强度与发音特征之间的关系。为量化口音强度,将语音的音素转录与基于词典的参考转录进行对比,计算音素层面的差异作为口音强度指标。所提框架利用最新的自监督学习发音反演技术,推断发音特征。通过对美国与英国英语朗读语料的分析,考察推导出的发音参数与口音强度代理变量之间的相关性,揭示系统性发音差异与口音强度指数的关联。结果显示,舌位模式可区分两种方言,尤其在卷舌音和后低元音方面存在显著跨方言差异。研究成果有助于自动化口音分析及语音处理中的发音建模。

原文摘要 · Abstract (English)

This paper explores the relationship between accent strength and articulatory features inferred from acoustic speech. To quantify accent strength, we compare phonetic transcriptions with transcriptions based on dictionary-based references, computing phoneme-level difference as a measure of accent strength. The proposed framework leverages recent self-supervised learning articulatory inversion techniques to estimate articulatory features. Analyzing a corpus of read speech from American and British English speakers, this study examines correlations between derived articulatory parameters and accent strength proxies, associating systematic articulatory differences with indexed accent strength. Results indicate that tongue positioning patterns distinguish the two dialects, with notable differences inter-dialects in rhotic and low back vowels. These findings contribute to automated accent analysis and articulatory modeling for speech processing applications.

口音分析发音建模自监督学习

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