How Linear Networks Enable Speaker‑Adaptive Speech Synthesis with Minimal Data
This article presents a linear‑network‑based speaker‑adaptation method for text‑to‑speech that achieves synthesis quality comparable to large‑scale training using only a few hundred target‑speaker utterances, and introduces a low‑rank‑plus‑diagonal compression to improve stability with scarce data.

