Instruct: Given a scientific paper title, retrieve paper titles that are cited by the given paper.
Query: Improving speech recognition in reverberation using a room-aware deep neural network and multi-task learning
The reverb challenge: A common evaluation framework for dereverberation and recognition of reverberant speech
Deep neural networks for acoustic modeling in speech recognition
Insights into deep neural networks for speaker recognition.
End-to-End Deep Neural Network for Automatic Speech Recognition
Towards End-to-End Speech Recognition with Deep Convolutional Neural Networks
Factored Deep Convolutional Neural Networks for Noise Robust Speech Recognition.
A Regression Approach to Speech Enhancement Based on Deep Neural Networks
Optimization Techniques to Improve Training Speed of Deep Neural Networks for Large Speech Tasks
Whispered speech recognition using deep denoising autoencoder
A Unified Deep Neural Network for Speaker and Language Recognition
Audio-visual deep learning for noise robust speech recognition
Whispered Speech Recognition Using Deep Denoising Autoencoder and Inverse Filtering
Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups
Ensemble Deep Learning for Speech Recognition
Improving speech recognition by revising gated recurrent units
Multitalker Speech Separation With Utterance-Level Permutation Invariant Training of Deep Recurrent Neural Networks
Reverberation robust acoustic modeling using i-vectors with time delay neural networks.
Towards End-To-End Speech Recognition with Recurrent Neural Networks
Very Deep Convolutional Neural Networks for Noise Robust Speech Recognition
An Experimental Study on Speech Enhancement Based on Deep Neural Networks
Multi-Objective Virtual Machine Placement in Virtualized Data Center Environments
Arsenic , Tobacco Smoke , and Occupation Associations of Multiple Agents with Lung and Bladder Cancer
Microplastics in Four Estuarine Rivers in the Chesapeake Bay, U.S.A.
Dynamic power allocation and routing for time-varying wireless networks
Learning from hints in neural networks