A two-stage replay-based post-training method corrects ASR timestamp drift across non-speech gaps while preserving recognition far better than ordinary timestamp fine-tuning.
SUPERB: Speech processing universal performance benchmark,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
REDDIT: Correcting Model-Generated Timestamp Drift in ASR without Forgetting via Replay-Based Distribution Editing
A two-stage replay-based post-training method corrects ASR timestamp drift across non-speech gaps while preserving recognition far better than ordinary timestamp fine-tuning.