198 citations · 276 across the 15 of their papers we have counts for
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eess.AS2021
LT-LM: a novel non-autoregressive language model for single-shot lattice rescoring
Anton Mitrofanov, Mariya Korenevskaya, Ivan Podluzhny +7
Neural network-based language models are commonly used in rescoring approaches to improve the quality of modern automatic speech recognition (ASR) systems. Most of the existing met…
eess.AS2021★ 12 cited
Dynamic Acoustic Unit Augmentation With BPE-Dropout for Low-Resource End-to-End Speech Recognition
Aleksandr Laptev, Andrei Andrusenko, Ivan Podluzhny +3
With the rapid development of speech assistants, adapting server-intended automatic speech recognition (ASR) solutions to a direct device has become crucial. Researchers and indust…