The End of Awkward AI Transcriptions - Travis Bartley and Myungjong Kim
Jun 3, 2025 · 16:24
NVIDIA speech AI researchers Travis Bartley, Myungjong Kim, and Jae-hun detail how their Fast Conformer backbone powers both streaming (Parakeet) and multitask (Canary) models, achieving top-5 Hugging Face ASR leaderboard rankings by prioritizing customization over one-size-fits-all. They explain CTC/TDT for low-latency streaming and attention encoder-decoder for high-accuracy multitask models, with Subformer enabling unified speaker diarization and target-speaker ASR. Training uses open-source and proprietary data with pseudo-labeling via the Nemo toolkit. Deployment on NVIDIA Riva NIM with TensorRT optimization supports low-latency streaming and offline processing. Customization includes fine-tuning acoustic models, language models, punctuation, and inverse text normalization for domain-specific terms like medical and food ordering.
