38 citations · 45 across the 7 of their papers we have counts for
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eess.AS2020★ 3 cited
Streaming Multi-speaker ASR with RNN-T
Ilya Sklyar, Anna Piunova, Yulan Liu
Recent research shows end-to-end ASR systems can recognize overlapped speech from multiple speakers. However, all published works have assumed no latency constraints during inferen…
eess.AS2020
Improving RNN-T ASR Accuracy Using Context Audio
Andreas Schwarz, Ilya Sklyar, Simon Wiesler
We present a training scheme for streaming automatic speech recognition (ASR) based on recurrent neural network transducers (RNN-T) which allows the encoder network to learn to exp…
eess.AS2020
Subword Regularization: An Analysis of Scalability and Generalization for End-to-End Automatic Speech Recognition
Egor Lakomkin, Jahn Heymann, Ilya Sklyar +1
Subwords are the most widely used output units in end-to-end speech recognition. They combine the best of two worlds by modeling the majority of frequent words directly and at the…