most citedBetter Pseudo-labeling with Multi-ASR Fusion and Error Correction by SpeechLLM

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cs.CL2025

Better Semi-supervised Learning for Multi-domain ASR Through Incremental Retraining and Data Filtering

Andres Carofilis, Pradeep Rangappa, Srikanth Madikeri +10

Fine-tuning pretrained ASR models for specific domains is challenging when labeled data is scarce. But unlabeled audio and labeled data from related domains are often available. We…

cs.CL2025

Efficient Data Selection for Domain Adaptation of ASR Using Pseudo-Labels and Multi-Stage Filtering

Pradeep Rangappa, Andres Carofilis, Jeena Prakash +10

Fine-tuning pretrained ASR models for specific domains is challenging for small organizations with limited labeled data and computational resources. Here, we explore different data…