Efficient ASR Training with Conversations that Never Happened 事件

Efficient ASR Training with Conversations that Never Happened arXiv:2606.03957v1 Announce Type: new Abstract: Conversational ASR for lower-resource languages and niche domains is limited by the scarcity of domain-matched multi-speaker training data. We propose an augmentation pipeline that generates scenario-level dialogues with participant metadata, maps speaker attributes to TTS voice profiles, and assembles synthesized utterances into speaker-aware simulated conversations. We evaluated five