More Balance Is Not More Accuracy: Rebalancing Rare Vocal Events Without Redesigning ASR
TL;DR for operators Speech systems that must preserve coughs, laughter, yawns, breathing, and similar signals face a familiar long-tail problem: rare events deserve more training attention, but increasing that attention can also disturb ordinary transcription and better-represented categories. Jia and colleagues test a deliberately data-centric answer in Long-Tail Rebalancing for Non-Verbal Vocalization-Aware ASR: A Track 1 System for the NVVSpeech Challenge.1 They keep the Qwen3-ASR 1.7B backbone, supervised objective, tokenizer, target format, and main optimization recipe fixed. What changes is the training distribution. ...