# Which Prosodic Features Matter Most for Pragmatics?

arXiv: https://arxiv.org/abs/2408.13240 · HTML: https://mlsanity.com/paper/2408.13240/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 38 references that are in the map.
- First posted on arXiv 23 Aug 2024.

## Builds on (most cited first, 10 of 10)

- [Seamless: Multilingual Expressive and Streaming Speech Translation](https://mlsanity.com/paper/2312.05187/) (2023)
- [On the Utility of Self-supervised Models for Prosody-related Tasks](https://mlsanity.com/paper/2210.07185/) (2022)
- [Spoken Language Interaction with Robots: Research Issues and Recommendations, Report from the NSF Future Directions Workshop](https://mlsanity.com/paper/2011.05533/) (2020)
- [Translatotron 3: Speech to Speech Translation with Monolingual Data](https://mlsanity.com/paper/2305.17547/) (2023)
- [Disentangling Prosody Representations with Unsupervised Speech Reconstruction](https://mlsanity.com/paper/2212.06972/) (2022)
- [CONCSS: Contrastive-based Context Comprehension for Dialogue-appropriate Prosody in Conversational Speech Synthesis](https://mlsanity.com/paper/2312.10358/) (2023)
- [Spontaneous Style Text-to-Speech Synthesis with Controllable Spontaneous Behaviors Based on Language Models](https://mlsanity.com/paper/2407.13509/) (2024)
- [Towards cross-language prosody transfer for dialog](https://mlsanity.com/paper/2307.04123/) (2023)
- [A Collection of Pragmatic-Similarity Judgments over Spoken Dialog Utterances](https://mlsanity.com/paper/2403.14808/) (2024)
- [Controllable Prosody Generation With Partial Inputs](https://mlsanity.com/paper/2303.09446/) (2023)

## Built on by (most cited first, 2 of 2)

- [Aligning Backchannel and Dialogue Context Representations via Contrastive LLM Fine-Tuning](https://mlsanity.com/paper/2604.16622/) (2026)
- [Towards Precision Characterization of Communication Disorders using Models of Perceived Pragmatic Similarity](https://mlsanity.com/paper/2409.09170/) (2024)

## Abstract (arXiv)

We investigate which prosodic features matter most in conveying prosodic functions. We use the problem of predicting human perceptions of pragmatic similarity among utterance pairs to evaluate the utility of prosodic features of different types. We find, for example, that duration-related features are more important than pitch-related features, and that utterance-initial features are more important than utterance-final features. Further, failure analysis indicates that modeling using pitch features only often fails to handle important pragmatic functions, and suggests that several generally-neglected acoustic and prosodic features are pragmatically significant, including nasality and vibrato. These findings can guide future basic research in prosody, and suggest how to improve speech synthesis evaluation, among other applications.