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Using Prosody to Predict Syntactic Structure

arXiv 2608.30260 ↗First posted 31 Aug 2026cs.CL cs.AI cs.LGcited by 0

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Abstract (arXiv)

While it is well-established that prosody carries crucial cues for syntactic structure, the degree and nature of correspondence between these two domains remains contested. We investigate the syntax-prosody interface through an information-theoretic lens, quantifying the interaction between prosodic features and syntactic representations as their mutual information. We provide a general-purpose framework for estimating this quantity over large speech-text corpora using multimodal language models. Our framework is structure-agnostic and modular, insofar as it can be used to measure the contributions of individual prosodic features or components of structure. We evaluate the syntax-prosody relationship for two features (word duration and inter-word pauses) across two domains--read audiobooks and spontaneous conversations--both in English. Our results demonstrate that prosody contains measurable syntactic information, with prosodic features reducing syntactic uncertainty in spontaneous conversations by up to 10.2%. Our findings offer new empirical support for several theoretical accounts of the syntax-prosody interface.

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References · 12

  1. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  2. 2023Vision-Language Models for Vision Tasks: A Surveycited by 839
  3. 2020Stanza: A Python Natural Language Processing Toolkit for Many Human Languagescited by 723
  4. 2019LibriTTS: A Corpus Derived from LibriSpeech for Text-to-Speechcited by 649
  5. 2020Information-Theoretic Probing for Linguistic Structurecited by 207
  6. 2019Meaning to Form: Measuring Systematicity as Informationcited by 16
  7. 2025Causal Estimation of Tokenisation Biascited by 16
  8. 2023Quantifying the redundancy between prosody and textcited by 12
  9. 2025The time scale of redundancy between prosody and linguistic contextcited by 4
  10. 2024Punctuation Restoration Improves Structure Understanding Without Supervisioncited by 3
  11. 2025Using Information Theory to Characterize Prosodic Typology: The Case of Tone, Pitch-Accent and Stress-Accentcited by 3
  12. 2025What Do Prosody and Text Convey? Characterizing How Meaningful Information is Distributed Across Multiple Channelscited by 3

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  1. 2024ProsodyFM: Unsupervised Phrasing and Intonation Control for Intelligible Speech Synthesis
  2. 2021On the Interplay Between Sparsity, Naturalness, Intelligibility, and Prosody in Speech Synthesis
  3. 2026Aligning Backchannel and Dialogue Context Representations via Contrastive LLM Fine-Tuning
  4. 2021Syntactic Perturbations Reveal Representational Correlates of Hierarchical Phrase Structure in Pretrained Language Models
  5. 2025Investigating Stochastic Methods for Prosody Modeling in Speech Synthesis
  6. 2026Causal Interventions Reveal Typologically Organized Syntactic Mechanisms in Multilingual Language Models
  7. 2026Gesture2Speech: How Far Can Hand Movements Shape Expressive Speech?
  8. 2026When Models Hear What They Expect: Diagnosing Prosodic Heuristics in Multimodal Sarcasm Detection