33 citations · 121 across the 12 of their papers we have counts for
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eess.AS2018★ 7 cited
Fine-tuning on Clean Data for End-to-End Speech Translation: FBK @ IWSLT 2018
Mattia Antonino Di Gangi, Roberto Dessì, Roldano Cattoni +2
This paper describes FBK's submission to the end-to-end English-German speech translation task at IWSLT 2018. Our system relies on a state-of-the-art model based on LSTMs and CNNs,…
cs.CL2018★ 11 cited
Deep Neural Machine Translation with Weakly-Recurrent Units
Mattia Antonino Di Gangi, Marcello Federico
Recurrent neural networks (RNNs) have represented for years the state of the art in neural machine translation. Recently, new architectures have been proposed, which can leverage p…