论文标题

探索英国口音:通过功能数据分析对陷阱浴进行建模

Exploring British Accents: Modelling the Trap-Bath Split with Functional Data Analysis

论文作者

Koshy, Aranya, Tavakoli, Shahin

论文摘要

我们演讲的声音受我们来自的地方的影响。英国包含多种独特的口音,这些口音吸引了语言学。特别是,在北部和南部,诸如“ class”之类的单词中的“ a”元音的发音不同。该元音的语音记录可以表示为增强曲线,也可以表示为Mel频率曲线系数曲线。功能数据分析和广义添加剂模型提供技术来建模这些曲线的变化。我们的第一个目的是通过训练本文收集的南北级别元音数据集的两个分类器(Koshy 2020)对典型的北部和南部元音 /AE /和 /A / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / /的区别进行建模(Koshy 2020)(Koshy 2020)(Koshy)),以建模。我们的第二个目的是想象英国的重音的地理变化。为此,我们使用第二个数据集的语音录音,即英国国家语料库(BNC)音频版(Coleman等,2012)。训练有素的模型用于预测BNC中说话者的口音,然后我们使用SOAP膜在这些预测中对地理模式进行建模。这项工作展示了一种在语音记录中建模语音重音变化的灵活和可解释的方法。

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 generalized additive models offer techniques to model the variation in these curves. Our first aim is to model the difference between typical Northern and Southern vowels /ae/ and /a/, by training two classifiers on the North-South Class Vowels dataset collected for this paper (Koshy 2020). Our second aim is to visualize geographical variation of accents in Great Britain. For this we use speech recordings from a second dataset, the British National Corpus (BNC) audio edition (Coleman et al. 2012). 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 modeling phonetic accent variation in speech recordings.

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