activity
20162023
most citedCompacting Neural Network Classifiers via Dropout Training

11 citations · 11 across the 4 of their papers we have counts for

collaborators
Showing 2020Show all

2 papers · 1 filter

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…