This paper introduces iterative pseudo-labeling to Mandarin-English code-switching ASR, showing gains from unlabeled data. The three-phase approach — pseudo-label generation, two-stage bilingual training, and iterative refinement — improves CS-ASR performance where labeled data is scarce. It matters for developers building ASR for mixed-language speech.
Opening Kapyn…