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Principled Hybrids of Generative and Discriminative Domain Adaptation
We propose a probabilistic framework for domain adaptation that blends b...
05/25/2017 ∙ by Han Zhao, et al. ∙0 ∙
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An Empirical Evaluation of Deep Learning on Highway Driving
Numerous groups have applied a variety of deep learning techniques to co...
04/07/2015 ∙ by Brody Huval, et al. ∙0 ∙
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Deep learning for class-generic object detection
We investigate the use of deep neural networks for the novel task of cla...
12/24/2013 ∙ by Brody Huval, et al. ∙0 ∙
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Cold Fusion: Training Seq2Seq Models Together with Language Models
Sequence-to-sequence (Seq2Seq) models with attention have excelled at ta...
08/21/2017 ∙ by Anuroop Sriram, et al. ∙0 ∙
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Exploring Neural Transducers for End-to-End Speech Recognition
In this work, we perform an empirical comparison among the CTC, RNN-Tran...
07/24/2017 ∙ by Eric Battenberg, et al. ∙0 ∙
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Reducing Bias in Production Speech Models
Replacing hand-engineered pipelines with end-to-end deep learning system...
05/11/2017 ∙ by Eric Battenberg, et al. ∙0 ∙
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Convolutional Recurrent Neural Networks for Small-Footprint Keyword Spotting
Keyword spotting (KWS) constitutes a major component of human-technology...
03/15/2017 ∙ by Sercan O. Arik, et al. ∙0 ∙
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Deep Voice: Real-time Neural Text-to-Speech
We present Deep Voice, a production-quality text-to-speech system constr...
02/25/2017 ∙ by Sercan O. Arik, et al. ∙0 ∙
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Active Learning for Speech Recognition: the Power of Gradients
In training speech recognition systems, labeling audio clips can be expe...
12/10/2016 ∙ by Jiaji Huang, et al. ∙0 ∙
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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...
12/08/2015 ∙ by Dario Amodei, et al. ∙0 ∙
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Deep Speech: Scaling up end-to-end speech recognition
We present a state-of-the-art speech recognition system developed using ...
12/17/2014 ∙ by Awni Hannun, et al. ∙0 ∙
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