1 citations · 1 across the 4 of their papers we have counts for
4 papers
Unifying Streaming and Non-streaming Zipformer-based ASR
Bidisha Sharma, Karthik Pandia Durai, Shankar Venkatesan +4
There has been increasing interest in unifying streaming and non-streaming automatic speech recognition (ASR) models to reduce development, training, and deployment costs. We prese…
Better Pseudo-labeling with Multi-ASR Fusion and Error Correction by SpeechLLM
Jeena Prakash, Blessingh Kumar, Kadri Hacioglu +5
Automatic speech recognition (ASR) models rely on high-quality transcribed data for effective training. Generating pseudo-labels for large unlabeled audio datasets often relies on…
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…
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…