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DEFINE framework decouples speaker identity and accent in zero-shot TTS

By PulseAugur Editorial · [1 sources] ·

Researchers have developed DEFINE, a novel end-to-end framework for zero-shot text-to-speech (TTS) that decouples speaker identity from accent control. By conditioning on separate audio exemplars for identity and target accent, DEFINE allows for continuous control over accent strength without retraining. The system, built upon F5-TTS with LoRA adaptation, demonstrated improved accent accuracy and generalization to unseen accents, matching the performance of more complex cascades while maintaining higher speaker similarity. AI

IMPACT This research advances zero-shot TTS capabilities by enabling independent control over speaker identity and accent, potentially leading to more versatile and controllable speech generation systems.

RANK_REASON The cluster contains a research paper detailing a new framework for text-to-speech synthesis. [lever_c_demoted from research: ic=1 ai=1.0]

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

DEFINE framework decouples speaker identity and accent in zero-shot TTS

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The cluster contains a research paper detailing a new framework for text-to-speech synthesis. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    DEFINE: Exemplar-Guided Accent Control for Zero-Shot TTS

    Zero-shot text-to-speech (TTS) can reproduce an unseen speaker from a short reference recording, but typically entangles speaker identity and accent within the same reference. We introduce DEFINE, an end-to-end framework that decouples these factors by conditioning speaker identi…

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