3 citations · 4 across the 3 of their papers we have counts for
3 papers
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…
Speed of Light Exact Greedy Decoding for RNN-T Speech Recognition Models on GPU
Daniel Galvez, Vladimir Bataev, Hainan Xu +1
The vast majority of inference time for RNN Transducer (RNN-T) models today is spent on decoding. Current state-of-the-art RNN-T decoding implementations leave the GPU idle ~80% of…
Powerful and Extensible WFST Framework for RNN-Transducer Losses
Aleksandr Laptev, Vladimir Bataev, Igor Gitman +1
This paper presents a framework based on Weighted Finite-State Transducers (WFST) to simplify the development of modifications for RNN-Transducer (RNN-T) loss. Existing implementat…