4 papers
Label-Looping: Highly Efficient Decoding for Transducers
Vladimir Bataev, Hainan Xu, Daniel Galvez +2
This paper introduces a highly efficient greedy decoding algorithm for Transducer-based speech recognition models. We redesign the standard nested-loop design for RNN-T decoding, s…
Nemotron-4 340B Technical Report
Nvidia, :, Bo Adler +80
We release the Nemotron-4 340B model family, including Nemotron-4-340B-Base, Nemotron-4-340B-Instruct, and Nemotron-4-340B-Reward. Our models are open access under the NVIDIA Open…
Fast Context-Biasing for CTC and Transducer ASR models with CTC-based Word Spotter
Andrei Andrusenko, Aleksandr Laptev, Vladimir Bataev +2
Accurate recognition of rare and new words remains a pressing problem for contextualized Automatic Speech Recognition (ASR) systems. Most context-biasing methods involve modificati…
Multi-blank Transducers for Speech Recognition
Hainan Xu, Fei Jia, Somshubra Majumdar +2
This paper proposes a modification to RNN-Transducer (RNN-T) models for automatic speech recognition (ASR). In standard RNN-T, the emission of a blank symbol consumes exactly one i…