The sound of our speech is influenced by the places we come from. Great Britain contains a wide variety of distinctive accents which are of interest to linguistics. In particular, the ‘a’ vowel in words like ‘class’ is pronounced differently in the North and the South. Speech recordings of this vowel can be represented as formant curves or as mel-frequency cepstral coefficient curves. Functional data analysis and generalised additive models offer techniques to model the variation in these curves. Our first aim was to model the difference between typical Northern and Southern vowels /æ/ and /ɑ/, by training two classifiers on the North-South Class Vowels dataset collected for this paper. Our second aim is to visualise geographical variation of accents in Great Britain. For this we use speech recordings from a second dataset, the British National Corpus (BNC) audio edition. The trained models are used to predict the accent of speakers in the BNC, and then we model the geographical patterns in these predictions using a soap film smoother. This work demonstrates a flexible and interpretable approach to modelling phonetic accent variation in speech recordings.

中文翻译：

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探索英国口音：使用功能数据分析模拟陷阱-浴缸分割

我们说话的声音受我们来自的地方的影响。大不列颠包含多种语言学感兴趣的独特口音。特别是，像“class”这样的词中的“a”元音在北方和南方的发音不同。该元音的语音记录可以表示为共振峰曲线或梅尔频率倒谱系数曲线。功能数据分析和广义相加模型提供了对这些曲线的变化进行建模的技术。我们的第一个目标是通过在为本文收集的南北类元音数据集上训练两个分类器来模拟典型的南北元音 /æ/ 和 /ɑ/ 之间的差异。我们的第二个目标是可视化英国口音的地理差异。为此，我们使用来自第二个数据集的语音记录，英国国家语料库 (BNC) 音频版。训练后的模型用于预测 BNC 中说话者的口音，然后我们使用更平滑的肥皂膜对这些预测中的地理模式进行建模。这项工作展示了一种灵活且可解释的方法来模拟语音记录中的语音重音变化。