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1
Deep neural network features and semi-supervised training for low resource speech recognition
In: http://www.clsp.jhu.edu/~samuel/pdfs/dnn_semisup_lr.pdf (2013)
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2
Deep neural network features and semi-supervised training for low resource speech recognition
In: http://hltcoe.jhu.edu/uploads/publications/papers/16656_slides.pdf (2013)
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3
Likelihood-maximizing beamforming for robust hands-free speech recognition
In: http://research.microsoft.com/en-us/um/redmond/groups/srg/papers/2004-mseltzer-sap.pdf (2004)
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4
Speech recognizer-based microphone array processing for robust hands-free speech recognition
In: http://www.cs.cmu.edu/~mseltzer/papers/icassp02_multimic.pdf (2002)
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5
Speech recognizer-based microphone array processing for robust hands-free speech recognition
In: http://www.cs.cmu.edu/~robust/Papers/multimic_unsupervised.pdf (2002)
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6
DEEP BEAMFORMING NETWORKS FOR MULTI-CHANNEL SPEECH RECOGNITION
In: https://www.microsoft.com/en-us/research/wp-content/uploads/2016/06/DeepBeamforming-ICASSP2016-1.pdf
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7
Towards a non-parametric acoustic model: An acoustic decision tree for observation probability calculation,” Interspeech 2008
In: http://www.cs.cmu.edu/~ychiu/ychiu_web_files/nonparametric.pdf
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8
RECENT ADVANCES IN DEEP LEARNING FOR SPEECH RESEARCH AT MICROSOFT
In: http://research.microsoft.com/pubs/188864/ICASSP-2013-OverviewMSRDeepLearning.pdf
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9
Towards a Non-Parametric Acoustic Model: An Acoustic Decision Tree for Observation Probability Calculation
In: http://research.microsoft.com/pubs/78716/ADT.pdf
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10
THE INFLUENCE OF PITCH AND NOISE ON THE DISCRIMINABILITY OF FILTERBANK FEATURES
In: http://www.slaney.org/malcolm/Microsoft/Slaney2014%28InfluencePitchNoiseFilterbankFeaturesAtInterspeech%29.pdf
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