Noise Perturbation for Supervised Speech Separation
Explore this paper's citation graph
- Type
- article
- Published
- 2016-04-01
- Cited by
- 31
- References
- 36
- Access
- Open access
- OpenAlex
- https://openalex.org/W26900194
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:15866349
Keywords
Computer science, Open Database Connectivity, Interface (matter), Parallel computing, Information retrieval
References
- Rectified Linear Units Improve Restricted Boltzmann Machines
- An algorithm that improves speech intelligibility in noise for normal-hearing listeners.
- Environment-specific noise suppression for improved speech intelligibility by cochlear implant users.
- Computational Auditory Scene Analysis: Principles, Algorithms, and Applications
- Factors influencing intelligibility of ideal binary-masked speech: implications for noise reduction.
- A General Flexible Framework for the Handling of Prior Information in Audio Source Separation
- The Diverse Environments Multi-channel Acoustic Noise Database (DEMAND): A database of multichannel environmental noise recordings
- Exploring Monaural Features for Classification-Based Speech Segregation
- Elastic spectral distortion for low resource speech recognition with deep neural networks
- Acoustic Modeling Using Deep Belief Networks
- Supervised and Unsupervised Speech Enhancement Using Nonnegative Matrix Factorization
- Towards Generalizing Classification Based Speech Separation
- Speech intelligibility in background noise with ideal binary time-frequency masking.
- Perceptual learning for speech in noise after application of binary time-frequency masks.
- An algorithm to improve speech recognition in noise for hearing-impaired listeners.
- Isolating the energetic component of speech-on-speech masking with ideal time-frequency segregation.
- Improving deep neural networks for LVCSR using rectified linear units and dropout
- Active-Set Newton Algorithm for Overcomplete Non-Negative Representations of Audio
- On Training Targets for Supervised Speech Separation
- An Experimental Study on Speech Enhancement Based on Deep Neural Networks
Cited by
- A Deep Ensemble Learning Method for Monaural Speech Separation
- Large-scale training to increase speech intelligibility for hearing-impaired listeners in novel noises.
- Long Short-Term Memory for Speaker Generalization in Supervised Speech Separation
- Speech Intelligibility Potential of General and Specialized Deep Neural Network Based Speech Enhancement Systems
- Auditory mask estimation by RPCA for monaural speech enhancement
- Using visual speech information and perceptually motivated loss functions for binary mask estimation
- A Comparison of Perceptually Motivated Loss Functions for Binary Mask Estimation in Speech Separation
- Supervised Speech Separation Based on Deep Learning: An Overview
- On Generalization of Supervised Speech Separation
- On generating mixing noise signals with basis functions for simulating noisy speech and learning dnn-based speech enhancement models
- The impact of exploiting spectro-temporal context in computational speech segregation.
- Deep neural network based monaural speech enhancement with sparse and low-rank decomposition
- The benefit of combining a deep neural network architecture with ideal ratio mask estimation in computational speech segregation to improve speech intelligibility
- A novel segmentation model for medical images with intensity inhomogeneity based on adaptive perturbation
- Audio speech enhancement using masks derived from visual speech
- A review of supervised learning algorithms for single channel speech enhancement
- Analysis of Speech Separation Methods based on Deep Learning
- Multiresolution Cochleagram Speech Enhancement Algorithm Using Improved Deep Neural Networks with Skip Connections
- Ideal ratio mask estimation using supervised DNN approach for target speech signal enhancement
- Behavioral Pattern Analysis between Bilingual and Monolingual Listeners’ Natural Speech Perception on Foreign-Accented English Language Using Different Machine Learning Approaches