UtterTune: LoRA-Based Target-Language Pronunciation Edit and Control in Multilingual Text-to-Speech
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Computer Science > Sound
Title:UtterTune: LoRA-Based Target-Language Pronunciation Edit and Control in Multilingual Text-to-Speech
Abstract:We propose UtterTune, a lightweight method for adapting a multilingual text-to-speech (TTS) system built on a large language model (LLM). It improves control of pronunciation in the target language while preserving performance in the others. Although LLM architectures have enabled TTS models to achieve remarkable naturalness, accurately modeling grapheme-to-phoneme (G2P) mapping and prosody remains challenging, especially when the model omits an explicit G2P module and directly processes minimally encoded text (e.g., byte-pair encoding). UtterTune leverages low-rank adaptation to enable the control of segmental pronunciation and pitch accent at the phoneme level for Japanese speech, the target language in this paper, while maintaining naturalness and speaker similarity in a zero-shot setting. Objective and subjective evaluations confirm its effectiveness.
| Comments: | 7 pages. This version adds a note on the precedence of the proposed token-based pronunciation-control method relative to a subsequent technical report, and links to the released code, training/evaluation data, LoRA weights, and audio samples |
| Subjects: | Sound (cs.SD); Computation and Language (cs.CL); Audio and Speech Processing (eess.AS) |
| Cite as: | arXiv:2508.09767 [cs.SD] |
| (or arXiv:2508.09767v3 [cs.SD] for this version) | |
| https://doi.org/10.48550/arXiv.2508.09767
arXiv-issued DOI via DataCite
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Submission history
From: Shuhei Kato Dr. [view email][v1] Wed, 13 Aug 2025 12:52:38 UTC (16 KB)
[v2] Tue, 16 Sep 2025 10:28:11 UTC (19 KB)
[v3] Thu, 9 Jul 2026 05:17:50 UTC (17 KB)
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