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Aleksandr Laptev

1 accepted papers

2023

Powerful and Extensible WFST Framework for Rnn-Transducer Losses

ICASSP 2023accepted

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 implementations of RNN-T use CUDA-related code, which is hard to extend and debug. WFSTs are easy to construct and extend, and allo…

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