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This study presents a significant advancement in computational linguistics by demonstrating that English homophones exhibit distinct, predictable phonetic realizations based on semantic context, even after normalizing for word duration. The research leverages quantitative analysis of 14,000 tokens from news broadcasts to reveal systematic acoustic differences that standard transcriptions obscure, offering new tools for speech processing and language modeling.
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Letters hide the truth from our eyes: English homophones have meaningfully different phonetic realizations

arXiv2 min read

arXiv:2608.26749v1 Announce Type: new Abstract: The distribution of spoken word duration of English homophones is known to co-vary with frequency of use. This study investigates whether other aspects of the phonetic realization of homophones also differ. A series of quantitative investigations of 14,000 homophone tokens in American television news broadcasts revealed that the tokens of homophone pairs such as \textit{weight} and \textit{wait} have different phonetic realizations, and that these can be predicted from their meanings in utterance context. These systematic differences remain even when taking duration-related variation into account. Time-normalized spectrograms emerged as an excellent tool for probing the fine details of phonetic realization, and obviate the need for phonetic transcriptions, which inevitably hide the phonetic truth from our eyes.

Abstract:The distribution of spoken word duration of English homophones is known to co-vary with frequency of use. This study investigates whether other aspects of the phonetic realization of homophones also differ. A series of quantitative investigations of 14,000 homophone tokens in American television news broadcasts revealed that the tokens of homophone pairs such as \textit{weight} and \textit{wait} have different phonetic realizations, and that these can be predicted from their meanings in utterance context. These systematic differences remain even when taking duration-related variation into account. Time-normalized spectrograms emerged as an excellent tool for probing the fine details of phonetic realization, and obviate the need for phonetic transcriptions, which inevitably hide the phonetic truth from our eyes.

Computation and Language (cs.CL)

arXiv:2608.26749 [cs.CL]

(or arXiv:2608.26749v1 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2608.26749 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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Full text under the publisher's open licence · 210 words

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