Step-Audio 2 integrates a latent audio encoder, reasoning-centric reinforcement learning, and discrete audio token generation into language modeling to deliver state-of-the-art performance on audio understanding and conversational benchmarks.
Wenetspeech: A 10000+ hours multi-domain mandarin corpus for speech recognition
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A survey that classifies non-intrusive ASR refinement methods into five categories, reviews domain adaptation and evaluation datasets, proposes standardized metrics, and identifies future research directions.
On-policy distillation from a Qwen-ASR teacher improves a 0.6B Ark-ASR model over supervised fine-tuning and a same-scale baseline on four of five ASR benchmarks using 100k hours of speech.
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Data-Efficient On-Policy Distillation for Automatic Speech Recognition
On-policy distillation from a Qwen-ASR teacher improves a 0.6B Ark-ASR model over supervised fine-tuning and a same-scale baseline on four of five ASR benchmarks using 100k hours of speech.