Instruct: Given a paper title, retrieve paper titles that are cited by the given paper
Query: Blind One-microphone Speech Separation: A Spectral Learning Approach
Blind separation of speech mixtures via time-frequency masking
Curriculum Learning Based Approaches for Noise Robust Speaker Recognition
Convolutive Blind Separation of Non-Stationary Sources
Bayesian Singing-Voice Separation
MaD TwinNet: Masker-Denoiser Architecture with Twin Networks for Monaural Sound Source Separation
Semi-blind source separation with multichannel variational autoencoder
Mmdenselstm: An Efficient Combination of Convolutional and Recurrent Neural Networks for Audio Source Separation
Exploring Monaural Features for Classification-Based Speech Segregation
Learning spectral mapping for speech dereverberation
Blind source separation by sparse decomposition in a signal dictionary
Adversarial Semi-Supervised Audio Source Separation Applied to Singing Voice Extraction
localization based stereo speech source separation using probabilistic time - frequency masking and deep neural networks .
Deep neural network based spectral feature mapping for robust speech recognition.
Investigating Generative Adversarial Networks based Speech Dereverberation for Robust Speech Recognition
Deep unsupervised learning from speech
looking to listen at the cocktail party : a speaker - independent audio - visual model for speech separation .
Ensemble modeling of denoising autoencoder for speech spectrum restoration.
Speech feature denoising and dereverberation via deep autoencoders for noisy reverberant speech recognition
separation of speech by computational auditory scene analysis .
Monaural Sound Source Separation by Nonnegative Matrix Factorization With Temporal Continuity and Sparseness Criteria
Distance Metric Learning with Application to Clustering with Side-Information
Technology as Experience
Recognition of Isolated Indian Sign Language Gesture in Real Time
Image Segmentation Using Disjunctive Normal Bayesian Shape and Appearance Models
Defining Leadership in a Changing Time