research
∙
12/28/2017
Topic Compositional Neural Language Model
We propose a Topic Compositional Neural Language Model (TCNLM), a novel ...
share
research
∙
11/05/2017
Robust Speech Recognition Using Generative Adversarial Networks
This paper describes a general, scalable, end-to-end framework that uses...
research
∙
08/21/2017
Cold Fusion: Training Seq2Seq Models Together with Language Models
Sequence-to-sequence (Seq2Seq) models with attention have excelled at ta...
research
∙
07/24/2017
Exploring Neural Transducers for End-to-End Speech Recognition
In this work, we perform an empirical comparison among the CTC, RNN-Tran...
research
∙
05/11/2017
Reducing Bias in Production Speech Models
Replacing hand-engineered pipelines with end-to-end deep learning system...
research
∙
03/01/2017
Gram-CTC: Automatic Unit Selection and Target Decomposition for Sequence Labelling
Most existing sequence labelling models rely on a fixed decomposition of...
research
∙
12/10/2016
Active Learning for Speech Recognition: the Power of Gradients
In training speech recognition systems, labeling audio clips can be expe...
research
∙
12/08/2015
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
We show that an end-to-end deep learning approach can be used to recogni...
research
∙
12/17/2014
Deep Speech: Scaling up end-to-end speech recognition
We present a state-of-the-art speech recognition system developed using ...
research
∙
09/01/2014