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This study demonstrates that speakers systematically adjust their pitch, timing, and intonation in response to emojis, allowing listeners to recover intended meanings with high accuracy. The research establishes a clear hierarchy where greater semantic differences between emojis correlate with increased prosodic divergence, effectively bridging the gap between digital text and spoken production. For researchers in natural language processing and speech synthesis, these findings offer a concrete pathway to integrating affective nuance into text-to-speech systems.
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The Prosody of Emojis

arXiv2 min read

arXiv:2508.00537v2 Announce Type: replace Abstract: 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.

Abstract: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.

Computation and Language (cs.CL)

arXiv:2508.00537 [cs.CL]

(or arXiv:2508.00537v2 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2508.00537 Focus to learn more arXiv-issued DOI via DataCite

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Full text under the publisher's open licence · 239 words

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