# The Prosody of Emojis

arXiv: https://arxiv.org/abs/2508.00537 · HTML: https://mlsanity.com/paper/2508.00537/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 13 of its 61 references that are in the map.
- First posted on arXiv 1 Aug 2025.

## Builds on (most cited first, 13 of 13)

- [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019)
- [Robust Speech Recognition via Large-Scale Weak Supervision](https://mlsanity.com/paper/2212.04356/) (2022)
- [MPNet: Masked and Permuted Pre-training for Language Understanding](https://mlsanity.com/paper/2004.09297/) (2020)
- [Seamless: Multilingual Expressive and Streaming Speech Translation](https://mlsanity.com/paper/2312.05187/) (2023)
- [Towards End-to-End Prosody Transfer for Expressive Speech Synthesis with Tacotron](https://mlsanity.com/paper/1803.09047/) (2018)
- [CommonAccent: Exploring Large Acoustic Pretrained Models for Accent Classification Based on Common Voice](https://mlsanity.com/paper/2305.18283/) (2023)
- [Cross-domain Neural Pitch and Periodicity Estimation](https://mlsanity.com/paper/2301.12258/) (2023)
- [Speech is More Than Words: Do Speech-to-Text Translation Systems Leverage Prosody?](https://mlsanity.com/paper/2410.24019/) (2024)
- [Quantifying the redundancy between prosody and text](https://mlsanity.com/paper/2311.17233/) (2023)
- [The Role of Prosody in Spoken Question Answering](https://mlsanity.com/paper/2502.05389/) (2025)
- [Prosody in Cascade and Direct Speech-to-Text Translation: a case study on Korean Wh-Phrases](https://mlsanity.com/paper/2402.00632/) (2024)
- [On the Context-Free Ambiguity of Emoji](https://mlsanity.com/paper/2201.06302/) (2022)
- [EmojiVoice: Towards long-term controllable expressivity in robot speech](https://mlsanity.com/paper/2506.15085/) (2025)

## Abstract (arXiv)

Prosodic features such as pitch, timing, and intonation are central to spoken communication, conveying emotion, intent, and discourse structure. In text-based settings, where these cues are absent, emojis act as visual surrogates that add affective and pragmatic nuance. This study examines how emojis influence prosodic realisation in speech and how listeners interpret prosodic cues to recover emoji meanings. Unlike previous work, we directly link prosody and emojis by analysing human speech data collected through a controlled elicited production task. Using Bayesian multilevel modelling, we show that speakers systematically adapt their prosody based on emoji cues, and that listeners can recover intended meanings significantly above chance. Furthermore, our results reveal a clear hierarchy in prosodic shifts: greater semantic differences between emojis correspond to increased prosodic divergence. These findings suggest that emojis are meaningful carriers of prosodic intent that bridge the gap between digital text and spoken production.