Code Switching Automatic Speech Recognition

Code-switching automatic speech recognition (CS-ASR) aims to build systems that accurately transcribe speech containing multiple languages interwoven within a single utterance. Current research focuses on improving model efficiency through knowledge distillation and exploring architectures like Mixture-of-Experts (MoE) and Conformer networks, often incorporating language identification modules and leveraging monolingual data through techniques such as gated datastores or textual augmentation. Advances in CS-ASR are crucial for bridging language barriers in diverse communities and enabling more inclusive applications of speech technology, particularly in areas with significant code-switching prevalence.