Phrase-Localized Language-Contrastive Guidance: Training-Free Localized Accent Control for Code-Switching Text-to-Speech

arXiv:2609.01016 · cs.CL, cs.SD · Submitted 2026-09-01 · Read on arXiv

cs.CL, cs.SD

Submitted: 2026-09-01

Updated: 2026-09-01

Comments: Accepted to EMNLP 2026 (Main Conference). Demo: https://saga1214.github.io/PhraseLocalizedLCG/

Project page: https://saga1214.github.io/PhraseLocalizedLCG

License: http://creativecommons.org/licenses/by/4.0/

The gist: Current speech synthesis struggles with code-switching, which mixes a foreign language phrase into a primary language utterance, causing the phrase to be spoken with the primary language's accent

Terminology

Abstract

Current speech synthesis struggles with code-switching, which mixes a foreign language phrase into a primary language utterance, causing the phrase to be spoken with the primary language's accent rather than its native one. We propose Phrase-Localized Language-Contrastive Guidance (LCG), a training-free inference framework that restores a native accent to code-switched phrases in cross-lingual text-to-speech. LCG replaces the single language guidance applied across the whole utterance with a separate guidance for each region, so each part is guided by its own language. To choose where to apply this localized guidance, we propose a self-attention probing technique that finds the phrase boundaries without external alignments. Together, these components generate speech in which each region carries the accent of its own language, requiring no fine-tuning or auxiliary models. Across diverse language pairs, LCG robustly increases the nativeness of the code-switched phrase while suppressing accent leakage, and preserving overall speaker identity and naturalness.

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