{"slug": "seam-spectral-embedding-alignment-and-merging-for-low-resource-tts", "title": "SEAM: Spectral Embedding Alignment and Merging for Low-Resource TTS", "summary": "Researchers introduced SEAM (Spectral Embedding Alignment and Merging), a zero-audio initialization method for expanding the vocabulary of conditional text-to-speech models without paired-audio fine-tuning. SEAM targets the bottleneck that extensive fine-tuning with paired audio creates for low-resource and cross-lingual TTS adaptation.", "body_md": "Expanding the vocabulary of conditional text-to-speech (TTS) models typically requires extensive fine-tuning with paired audio, creating a major bottleneck for low-resource and cross-lingual adaptation. To address this, we introduce SEAM, a zero-audio initialization method that constructs embeddings", "url": "https://wpnews.pro/news/seam-spectral-embedding-alignment-and-merging-for-low-resource-tts", "canonical_source": "https://aiflash.com/news/137823/", "published_at": "2026-10-23 04:00:18+00:00", "updated_at": "2026-10-23 04:11:29.521119+00:00", "lang": "en", "topics": ["artificial-intelligence", "machine-learning", "natural-language-processing", "ai-research"], "entities": ["SEAM"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/seam-spectral-embedding-alignment-and-merging-for-low-resource-tts", "markdown": "https://wpnews.pro/news/seam-spectral-embedding-alignment-and-merging-for-low-resource-tts.md", "text": "https://wpnews.pro/news/seam-spectral-embedding-alignment-and-merging-for-low-resource-tts.txt", "jsonld": "https://wpnews.pro/news/seam-spectral-embedding-alignment-and-merging-for-low-resource-tts.jsonld"}}