Deterministic Prompting for Speaker-Stable Low-Resource Greek TTS
Modern TTS systems approach human quality for high-resource languages but degrade when clean speech data is scarce. Modern Greek exemplifies this, lacking the curated corpora behind state-of-the-art synthesis. We propose a data curation recipe that transforms audiobook recordings into TTS-ready data via WhisperX alignment and filtering. Then we fine-tune Parler-TTS (880M), a prompt-based multilingual model whose pre-training encodes phonetic priors transferable to Greek. During development, we find that LLM-generated style prompts introduce speaker drift at inference. Replacing them with deterministic prompts resolves this, and a speaker-specific LoRA stage trained on 3.5 h of single-spea...
| Authors | Georgios Syllas, Efthymios Georgiou, Kosmas Kritsis et al. |
|---|---|
| Primary category | cs.SD |
| Published | 9 September 2026 |
| Last updated at source | 9 September 2026 |
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