---
title: "What Do Prosody and Text Convey? Characterizing How"
description: "Earlier information-theoretic studies measured only how much text and prosody overlap overall. 86 references."
authors: ["Aditya Yadavalli", "Tiago Pimentel", "Tamar I Regev", "Ethan Gotlieb Wilcox", "Alex Warstadt"]
year: 2026
venue: "Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)"
source: "https://aclanthology.org/2026.acl-long.1085/"
doi: "10.18653/v1/2026.acl-long.1085"
licence: "CC BY 4.0 (ACL Anthology)"
licence_url: "https://creativecommons.org/licenses/by/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/yadavalli-2026-what-do-prosody-text-convey/"
---
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# What Do Prosody and Text Convey? Characterizing How Meaningful Information is Distributed Across Multiple Channels

**Authors:** [Aditya Yadavalli](https://md.research.elamur.ai/free/en/authors/aditya-yadavalli/), [Tiago Pimentel](https://md.research.elamur.ai/free/en/authors/tiago-pimentel/), Tamar I Regev, [Ethan Gotlieb Wilcox](https://md.research.elamur.ai/free/en/authors/ethan-wilcox/) and [Alex Warstadt](https://md.research.elamur.ai/free/en/authors/alex-warstadt/) · **Year:** 2026 · **Venue:** [Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)](https://md.research.elamur.ai/free/en/venues/acl/) ([ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/)) · **Publisher:** [Association for Computational Linguistics](https://md.research.elamur.ai/free/en/publishers/association-for-computational-linguistics/) · **Licence:** [CC BY 4.0 (ACL Anthology)](https://creativecommons.org/licenses/by/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/2026.acl-long.1085/) · [PDF](https://aclanthology.org/2026.acl-long.1085.pdf) · [DOI 10.18653/v1/2026.acl-long.1085](https://doi.org/10.18653/v1/2026.acl-long.1085) · [OpenAlex](https://openalex.org/W4417531161)

**Citations:** 0 citations (OpenAlex, 2026-10-14)

## Summary
Written text drops prosody, the pitch, timing and loudness of speech. Earlier information-theoretic studies measured only how much text and prosody overlap overall. They did not show what prosody contributes beyond the words. This paper estimates how information about a specific meaning dimension Y is split between text and audio. The dimensions studied are sarcasm, emotion and questionhood. Following Pimentel et al. (2020), mutual information is computed as the entropy of Y minus the cross-entropy loss of classifiers fine-tuned to predict Y. Audio classifiers are built on spoken language models such as Whisper, and text classifiers on language models such as GPT-2. No architecture accepts prosody alone, so the full audio signal stands in for it. Audio information not recoverable from text, MI(Y; A | T), approximates prosody's unique contribution. The data are English single-sentence utterances from television and podcasts. When context is limited to one sentence, audio carries roughly ten times more information than text about sarcasm and emotion. For questionhood the gain is much smaller. The framework can be extended to other meanings, channels and languages.

## Key points
- For sarcasm and emotion, audio carries more than ten times the information that text does, measured without context beyond the current sentence.
- For questionhood, audio gives only about 2.4 times the information of text, since wording and punctuation already signal questions strongly.
- The framework decomposes H(Y) into terms such as MI(Y; T), MI(Y; A) and MI(Y; A | T). MI(Y; A | T) is used as a proxy for MI(Y; P | T).
- Several factors shape the absolute estimates:
  - The sarcasm data are balanced between sarcastic and non-sarcastic utterances.
  - The emotion data assign one of ten discrete labels per utterance.
  - Text models were capped at GPT-2 XL size because of compute limits.
- The study covers English only, and the code is released at github.com/AdityaYadavalli1/convey-prosody.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

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## Cite

Cite as: Aditya Yadavalli, Tiago Pimentel, Tamar I Regev, Ethan Gotlieb Wilcox and Alex Warstadt. 2026. What Do Prosody and Text Convey? Characterizing How Meaningful Information is Distributed Across Multiple Channels. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@inproceedings{yadavalli2026what,
  title = {{What Do Prosody and Text Convey? Characterizing How Meaningful Information is Distributed Across Multiple Channels}},
  author = {Aditya Yadavalli, Tiago Pimentel, Tamar I Regev, Ethan Gotlieb Wilcox and Alex Warstadt},
  booktitle = {Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  year = {2026},
  doi = {10.18653/v1/2026.acl-long.1085},
  url = {https://doi.org/10.18653/v1/2026.acl-long.1085}
}
```

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