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This research demonstrates how contextual word embeddings can predict fine-grained acoustic details in spontaneous Mandarin speech, revealing deep semantic influences on articulation dynamics beyond standard phonetic controls. By linking meaning directly to formant trajectories via generalized additive models, the study challenges modular views of speech production and offers new insights for natural language understanding systems that process real-world audio.
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Word meaning co-determines vowel-inherent spectral change. A corpus-based investigation of conversational Mandarin

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arXiv:2607.21391v1 Announce Type: new Abstract: This study investigates vowel-inherent spectral change (VISC) in spontaneous conversational Mandarin. Using the generalized additive model and word embeddings from distributional semantics, we show that, when controlling for variables such as vowel duration, gender, speaker identity, co-articulation, vowel identity, and utterance position, vowel formant trajectory dynamics have word-specific components that are tied to their meaning in context: The F1 and F2 trajectories of words can be predicted from their contextualized embeddings with an accuracy that substantially exceeds a permutation baseline. Challenging modular cognitive models of speech production, these results indicate that, words' semantics co-determine the fine details of their articulation.

Title:Word meaning co-determines vowel-inherent spectral change. A corpus-based investigation of conversational Mandarin

Abstract:This study investigates vowel-inherent spectral change (VISC) in spontaneous conversational Mandarin. Using the generalized additive model and word embeddings from distributional semantics, we show that, when controlling for variables such as vowel duration, gender, speaker identity, co-articulation, vowel identity, and utterance position, vowel formant trajectory dynamics have word-specific components that are tied to their meaning in context: The F1 and F2 trajectories of words can be predicted from their contextualized embeddings with an accuracy that substantially exceeds a permutation baseline. Challenging modular cognitive models of speech production, these results indicate that, words' semantics co-determine the fine details of their articulation.

Computation and Language (cs.CL)

arXiv:2607.21391 [cs.CL]

(or arXiv:2607.21391v1 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2607.21391 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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