Voicing Personas: Rewriting Persona Descriptions into Style Prompts for Controllable Text-to-Speech

ACL ARR 2025 May Submission2503 Authors

Abstract:

In this paper, we propose a novel framework to control voice style in prompt-based, controllable text-to-speech systems by leveraging textual personas as voice style prompts.
We present two persona rewriting strategies to transform generic persona descriptions into speech-oriented prompts, enabling fine-grained manipulation of prosodic attributes such as pitch, emotion, and speaking rate.
Experimental results demonstrate that our methods enhance the naturalness, clarity, and consistency of synthesized speech.
Finally, we analyze implicit social biases introduced by LLM-based rewriting, with a focus on gender.
We underscore voice style as a crucial factor for persona-driven AI dialogue systems.

Paper Type: Short

Research Area: Speech Recognition, Text-to-Speech and Spoken Language Understanding

Research Area Keywords: persona, text-to-speech, controllable tts

Contribution Types: NLP engineering experiment

Languages Studied: English

Submission Number: 2503