arXiv cs.CL
· Papers
Reinforcement Learning for Data-Efficient Code-Switched ASR
arXiv:2607.02757v1 Announce Type: new Abstract: Audio-language models can be prompted for code-switched speech, but their decoding is not optimized for code-switching and often fails at language boundaries. We propose a practical reinforcement learning with verifiable rewards recipe for data-efficient adaptation of aud