autoregressive asr 1catastrophic forgetting 1replay-based editing 1self-supervised correction 1timestamp drift 1
From the 1 of 3 linked papers with an AI index.
3 papers
cs.CL2026
REDDIT: Correcting Model-Generated Timestamp Drift in ASR without Forgetting via Replay-Based Distribution Editing
Cheng-Kang Chou, Ming-To Chuang, Ke-Han Lu +2
The paper investigates drift in model-generated timestamps for autoregressive ASR systems and introduces REDDIT, a replay‑based distribution editing post‑training method that corre…
cs.CL2025
A Self-Refining Framework for Enhancing ASR Using TTS-Synthesized Data
Cheng-Kang Chou, Chan-Jan Hsu, Ho-Lam Chung +5
We propose a self-refining framework that enhances ASR performance with only unlabeled datasets. The process starts with an existing ASR model generating pseudo-labels on unannotat…
cs.SD2025
Channel-Aware Domain-Adaptive Generative Adversarial Network for Robust Speech Recognition
Chien-Chun Wang, Li-Wei Chen, Cheng-Kang Chou +3
While pre-trained automatic speech recognition (ASR) systems demonstrate impressive performance on matched domains, their performance often degrades when confronted with channel mi…