---
title: "Voice and Choice — paper by Szekely et al. (2024)"
description: "The paper asks whether the way an indirect request sounds, apart from its wording, changes how polite… 38 references, cited by 1 paper here."
authors: ["Eva Szekely", "Jeff Higginbotham", "Francesco Possemato"]
year: 2024
venue: "Proceedings of the 25th Annual Meeting of the Special Interest Group on Discourse and Dialogue"
source: "https://aclanthology.org/2024.sigdial-1.40/"
doi: "10.18653/v1/2024.sigdial-1.40"
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/szekely-2024-voice-choice-investigating-role-prosodic/"
---
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# Voice and Choice: Investigating the Role of Prosodic Variation in Request Compliance and Perceived Politeness Using Conversational TTS

**Authors:** [Eva Szekely](https://md.research.elamur.ai/free/en/authors/eva-szekely/), Jeff Higginbotham and Francesco Possemato · **Year:** 2024 · **Venue:** [Proceedings of the 25th Annual Meeting of the Special Interest Group on Discourse and Dialogue](https://md.research.elamur.ai/free/en/venues/sigdial/) ([SIGDIAL 2024](https://md.research.elamur.ai/free/en/venues/sigdial/2024/)) · **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/2024.sigdial-1.40/) · [PDF](https://aclanthology.org/2024.sigdial-1.40.pdf) · [DOI 10.18653/v1/2024.sigdial-1.40](https://doi.org/10.18653/v1/2024.sigdial-1.40) · [OpenAlex](https://openalex.org/W4402714990)

**Citations:** 2 citations (OpenAlex, 2026-10-14) · 1 in our library, of the 149,439 papers whose bibliographies we read

## Summary
The paper asks whether the way an indirect request sounds, apart from its wording, changes how polite it seems and whether listeners would grant it. To control prosody precisely without relying on voice actors, the authors trained a multi-speaker conversational TTS on spontaneous speech, based on a modified Tacotron 2 with utterance-level prosody control. It produces female, male and perceptually gender-ambiguous voices. Before use, the stimuli were checked with objective measures for naturalness, gender ambiguity and real acoustic differences between conditions. Two online crowd-sourced listening tests followed. In the first, listeners rated the politeness of permission and action requests. In the second, they heard pairs of differently rendered requests and chose the one they would more readily grant. A faster speech rate and higher vocal effort both raised willingness to comply, with effect sizes that depended on the voice's gender. Perceived politeness strongly predicted compliance, more so for the male voice. These findings matter for dialogue systems and for Augmentative Communication Technologies, whose users depend on TTS to make requests appropriately.

## Key points
- The TTS was trained on two spontaneous-speech corpora. The first is AptSpeech, about 8 h in total (2h 26min read, 5h 40min spontaneous, from a male General American moderator). The second is built from 14h 43min of conversational podcast recordings.
- Prosody was manipulated along two axes: speech rate (normal vs fast) and vocal effort (low, medium, high). These were crossed with three speaker profiles and two request types (permission vs action).
- In the per-voice ordinal regressions on compliance, a difference in vocal effort had its largest effect for the male voice (coefficient 0.62), compared with 0.40 for female and 0.32 for ambiguous. Speech rate mattered most for the ambiguous voice (0.38).
- In the combined analysis, Experiment 1 politeness scores were added to the Experiment 2 model as a predictor:
  - Politeness difference was the strongest effect (0.88).
  - Speech rate (0.28) and vocal effort (0.32) still had significant effects of their own.
  - For action requests, vocal effort helped more and politeness helped less (interaction −0.39).
- Stated limitation: there was only one voice per gender profile. The authors plan voice conversion to add variety and want to test richer features such as pauses, emphasis and final intonation.

## Interesting ideas
- Using a controllable synthesizer to build minimal-pair stimuli removes actor-to-actor variability, so one factor can change while everything else stays fixed. This is a clean way to test causal influence of a single cue.
- Asking people to choose between two items, instead of rating each on a scale, gives more sensitive judgements and avoids scale drift between raters.
- Feeding the averaged result of one experiment (politeness) into the model of another (compliance) separates a cue's direct effect from the part that works through an intermediate judgement.
- Permission requests and action requests responded differently to the same cues, which suggests that request subtype is a meaningful distinction.
- Every generated stimulus was checked with objective measures before it reached humans, to confirm the intended manipulation was actually present.

## For Mova

How these ideas could serve Mova, our small open language model — its files, stages and tests:

- **I1** (learn): generate sentence minimal pairs that differ in exactly one marker (a modal, "please", or the imperative vs interrogative form) and check that only the expected parts of the analysis shift, with unchanged pairs serving as negative controls.
- **I2** (learn): when an LLM teacher grades competing parses or frame readings, ask it which of two candidates is better rather than requesting absolute scores.
- **I3** (frames): keep perceived politeness as an explicit, explainable intermediate variable in request frames, so the system can show whether a request succeeds because of its politeness or despite it.
- **I4** (frames): split the request speech act in prag into permission and action subtypes so later reasoning about likely compliance can treat them differently.
- **I5** (back): automatically verify generated text, for example by re-parsing it, to confirm the intended meaning difference survived before the output is used or shown.

*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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- [University of Groningen](https://md.research.elamur.ai/free/en/universities/university-of-groningen/) — University, Groningen, Netherlands · 70 works · 5,142 citations
- [KTH Royal Institute of Technology](https://md.research.elamur.ai/free/en/universities/kth-royal-institute-of-technology/) — University, Stockholm, Sweden · 18 works · 788 citations
- [University at Buffalo, State University of New York](https://md.research.elamur.ai/free/en/universities/university-at-buffalo-state-university-of-new-york/) — University, Buffalo, United States · 12 works · 318 citations

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## Cite

Cite as: Eva Szekely, Jeff Higginbotham and Francesco Possemato. 2024. Voice and Choice: Investigating the Role of Prosodic Variation in Request Compliance and Perceived Politeness Using Conversational TTS. Proceedings of the 25th Annual Meeting of the Special Interest Group on Discourse and Dialogue.

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

```bibtex
@inproceedings{szekely2024voice,
  title = {{Voice and Choice: Investigating the Role of Prosodic Variation in Request Compliance and Perceived Politeness Using Conversational TTS}},
  author = {Eva Szekely, Jeff Higginbotham and Francesco Possemato},
  booktitle = {Proceedings of the 25th Annual Meeting of the Special Interest Group on Discourse and Dialogue},
  year = {2024},
  doi = {10.18653/v1/2024.sigdial-1.40},
  url = {https://doi.org/10.18653/v1/2024.sigdial-1.40}
}
```

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- [↑ back to papers of 2024](https://md.research.elamur.ai/free/en/papers/2024/page/12/)

## References

38 references, 1 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

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*Updated 1 November 2026*