In this work, we investigate pronunciation differences in English spoken by
Singaporean children in relation to their American and British counterparts by
conducting Kmeans clustering and Archetypal analysis on selected vowel pairs
and approximants. Given that Singapore adopts British English as the
institutional standard due to historical reasons, one might expect Singaporean
children to follow British pronunciation patterns. Indeed, Singaporean and
British children are more similar in their production of syllable-final /r/ --
they do not lower their third formant nearly as much as American children do,
suggesting a lack of rhoticity. Interestingly, Singaporean children also
present similar patterns to American children when it comes to their fronting
of vowels as demonstrated across various vowels including TRAP-BATH split
vowels. Singaporean children's English also demonstrated characteristics that
do not resemble any of the other two populations. We observe that Singaporean
children's vowel height characteristics are distinct from both that of American
and British children. In tense and lax vowel pairs, we also consistently
observe that the distinction is less conspicuous for Singaporean children
compared to the other speaker groups. Further, while American and British
children demonstrate lowering of F1 and F2 formants in transitions into
syllable-final /l/s, a wide gap between F2 and F3 formants, and small
difference between F1 and F2 formants, all of these are not exhibited in
Singaporean children's pronunciation. These findings point towards potential
sociolinguistic implications of how Singapore English might be evolving to
embody more than British pronunciation characteristics. Furthermore, these
findings also suggest that Singapore English could be have been influenced by
languages beyond American and British English, potentially due to Singapore's
multilingual environment.

本研究通过对新加坡儿童与美国、英国儿童英语发音的比较研究，使用 Kmeans 聚类和原型分析等方法，探究了新加坡英语流派的特点以及其与美国、英国英语流派之间的异同，并发现新加坡英语的元音高度特点独具特色。

新加坡儿童英语发音的大规模声学表征

Large-Scale Acoustic Characterization of Singaporean Children's English Pronunciation

Variation in speech is often quantified by comparing phonetic transcriptions
of the same utterance. However, manually transcribing speech is time-consuming
and error prone. As an alternative, therefore, we investigate the extraction of
acoustic embeddings from several self-supervised neural models. We use these
representations to compute word-based pronunciation differences between
non-native and native speakers of English, and between Norwegian dialect
speakers. For comparison with several earlier studies, we evaluate how well
these differences match human perception by comparing them with available human
judgements of similarity. We show that speech representations extracted from a
specific type of neural model (i.e. Transformers) lead to a better match with
human perception than two earlier approaches on the basis of phonetic
transcriptions and MFCC-based acoustic features. We furthermore find that
features from the neural models can generally best be extracted from one of the
middle hidden layers than from the final layer. We also demonstrate that neural
speech representations not only capture segmental differences, but also
intonational and durational differences that cannot adequately be represented
by a set of discrete symbols used in phonetic transcriptions.

研究使用自我监督的神经模型从语音中提取声学嵌入，计算非英语母语和英语母语以及挪威方言发音之间的基于单词的差异，并发现使用转换器的神经模型提取的语音表示与人类感知匹配得更好。