Speech Recognition Breakthrough
Daniel shares surprising insights into the efficiency of modern speech-to-text models, highlighting a significant leap in processing speed thanks to a CUDA-based decoder. Initially facing a daunting task of transcribing 50,000 hours of audio, the team managed to reduce the time needed to just 48 hours, showcasing a remarkable advancement in technology that promises reusable benefits for future projects.In this clip
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The AI Podcast
MLCommons’ David Kanter, NVIDIA’s Daniel Galvez on Publicly Accessible Datasets - Ep. 167
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