SyRA-CS: Synthetic-to-Real Adaptation for Code-Switched ASR with Meta-Learning

Paper recorded by Signals 4 on 2026-10-22 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-22 on arXiv · recorded by Signals 4 on 2026-10-23

Category: cs.CL · 自然语言处理 · first seen 2026-10-23

Abstract

Code-switched (CS) automatic speech recognition (ASR) remains difficult because real CS speech is scarce and synthetic speech does not fully match it. We investigate whether synthetic CS speech is more useful for learning an adaptation-friendly initialization than for ordinary continual fine-tuning. We propose SyRA-CS, a pair-specific synthetic-to-real adaptation framework based on Reptile meta-le

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