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08/21/2017
Cold Fusion: Training Seq2Seq Models Together with Language Models
Sequence-to-sequence (Seq2Seq) models with attention have excelled at ta...
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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...
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05/25/2017
Principled Hybrids of Generative and Discriminative Domain Adaptation
We propose a probabilistic framework for domain adaptation that blends b...
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05/11/2017
Reducing Bias in Production Speech Models
Replacing hand-engineered pipelines with end-to-end deep learning system...
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03/15/2017
Convolutional Recurrent Neural Networks for Small-Footprint Keyword Spotting
Keyword spotting (KWS) constitutes a major component of human-technology...
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02/25/2017
Deep Voice: Real-time Neural Text-to-Speech
We present Deep Voice, a production-quality text-to-speech system constr...
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12/10/2016
Active Learning for Speech Recognition: the Power of Gradients
In training speech recognition systems, labeling audio clips can be expe...
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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...
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04/07/2015
An Empirical Evaluation of Deep Learning on Highway Driving
Numerous groups have applied a variety of deep learning techniques to co...
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12/17/2014
Deep Speech: Scaling up end-to-end speech recognition
We present a state-of-the-art speech recognition system developed using ...
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12/24/2013