14.5k citations · 90.1k across the 347 of their papers we have counts for
5 papers · 2 filters
End-to-End Attention-based Large Vocabulary Speech Recognition
Dzmitry Bahdanau, Jan Chorowski, Dmitriy Serdyuk +2
Many of the current state-of-the-art Large Vocabulary Continuous Speech Recognition Systems (LVCSR) are hybrids of neural networks and Hidden Markov Models (HMMs). Most of these sy…
Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models
Iulian V. Serban, Alessandro Sordoni, Yoshua Bengio +2
We investigate the task of building open domain, conversational dialogue systems based on large dialogue corpora using generative models. Generative models produce system responses…
Attention-Based Models for Speech Recognition
Jan Chorowski, Dzmitry Bahdanau, Dmitriy Serdyuk +2
Recurrent sequence generators conditioned on input data through an attention mechanism have recently shown very good performance on a range of tasks in- cluding machine translation…
Learning to Understand Phrases by Embedding the Dictionary
Felix Hill, Kyunghyun Cho, Anna Korhonen +1
Distributional models that learn rich semantic word representations are a success story of recent NLP research. However, developing models that learn useful representations of phra…
On Using Monolingual Corpora in Neural Machine Translation
Caglar Gulcehre, Orhan Firat, Kelvin Xu +6
Recent work on end-to-end neural network-based architectures for machine translation has shown promising results for En-Fr and En-De translation. Arguably, one of the major factors…