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Deep neural networks have shown excellent prospects in speech separation tasks.
Some experiments on the recognition of speech, with one and with two ears
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Csr-i (wsj0) complete ldc93s6a
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The cocktail party phenomenon revisited: attention and memory in the classic selective listening procedure of cherry (1953)
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Adam Gazzaley, Jeffrey W Cooney, Kevin McEvoy, Robert T Knight, and Mark D’esposito · 2005
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The cocktail party problem
Simon Haykin and Zhe Chen · 2005
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Attention to simultaneous unrelated auditory and visual events: behavioral and neural correlates
Jennifer A Johnson and Robert J Zatorre · 2005
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Performance measurement in blind audio source separation
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Updated energy budgets for neural computation in the neocortex and cerebellum
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Selective cortical representation of attended speaker in multi-talker speech perception
Nima Mesgarani and Edward F Chang · 2012
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Structural and functional brain networks: from connections to cognition
Hae-Jeong Park and Karl Friston · 2013
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The cocktail-party problem revisited: early processing and selection of multi-talker speech
Adelbert W Bronkhorst · 2015
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Top-down attention regulates the neural expression of audiovisual integration
Luis Morís Fernández, Maya Visser, Noelia Ventura-Campos, César Ávila, and Salvador Soto-Faraco · 2015
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2015
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Librispeech: an asr corpus based on public domain audio books
Vassil Panayotov, Guoguo Chen, Daniel Povey, and Sanjeev Khudanpur · 2015
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Rupesh Kumar Srivastava, Klaus Greff, and Jürgen Schmidhuber · 2015
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Attention to scale: Scale-aware semantic image segmentation
Liang-Chieh Chen, Yi Yang, Jiang Wang, Wei Xu, and Alan L Yuille · 2016
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Deep clustering: discriminative embeddings for segmentation and separation
John R Hershey, Zhuo Chen, Jonathan Le Roux, and Shinji Watanabe · 2016
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Deep attractor network for single-microphone speaker separation
Zhuo Chen, Yi Luo, and Nima Mesgarani · 2017
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Densely connected convolutional networks
Conv-tasnet: Surpassing ideal time–frequency magnitude masking for speech separation
Yi Luo and Nima Mesgarani · 2019
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Which ones are speaking? speaker-inferred model for multi-talker speech separation
Jing Shi, Jiaming Xu, and Bo Xu · 2019
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WHAM!: Extending Speech Separation to Noisy Environments
Gordon Wichern, Joe Antognini, Michael Flynn, Licheng Richard Zhu, Emmett McQuinn, Dwight Crow, Ethan Manilow, and Jonathan Le Roux · 2019
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Dual-Path Transformer Network: Direct Context-Aware Modeling for End-to-End Monaural Speech Separation
Jingjing Chen, Qirong Mao, and Dong Liu · 2020
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Librimix: an open-source dataset for generalizable speech separation
Joris Cosentino, Manuel Pariente, Samuele Cornell, Antoine Deleforge, and Emmanuel Vincent · 2020
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Gao Huang, Zhuang Liu, Laurens Van Der Maaten, and Kilian Q Weinberger · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Permutation invariant training of deep models for speaker-independent multi-talker speech separation
Dong Yu, Morten Kolbæk, Zheng-Hua Tan, and Jesper Jensen · 2017
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Deep audio-visual speech recognition
Triantafyllos Afouras, Joon Son Chung, Andrew Senior, Oriol Vinyals, and Andrew Zisserman · 2018
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Role of the right inferior parietal cortex in auditory selective attention: An rtms study
Corinne A Bareham, Stanimira D Georgieva, Marc R Kamke, David Lloyd, Tristan A Bekinschtein, and Jason B Mattingley · 2018
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Squeeze-and-excitation networks
Jie Hu, Li Shen, and Gang Sun · 2018
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Tasnet: time-domain audio separation network for real-time, single-channel speech separation
Yi Luo and Nima Mesgarani · 2018
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Dual-path rnn: efficient long sequence modeling for time-domain single-channel speech separation
Yi Luo, Zhuo Chen, and Takuya Yoshioka · 2020
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Asteroid: the PyTorch-based audio source separation toolkit for researchers
Manuel Pariente, Samuele Cornell, Joris Cosentino, Sunit Sivasankaran, Efthymios Tzinis, Jens Heitkaemper, Michel Olvera, Fabian-Robert Stöter, Mathieu Hu, Juan M. Martín-Doñas, David Ditter, Ariel Frank, Antoine Deleforge, and Emmanuel Vincent · 2020
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Multi-scale self-guided attention for medical image segmentation
Ashish Sinha and Jose Dolz · 2020
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Sudo rm-rf: efficient networks for universal audio source separation
Efthymios Tzinis, Zhepei Wang, and Paris Smaragdis · 2020
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Speech separation using an asynchronous fully recurrent convolutional neural network
Xiaolin Hu, Kai Li, Weiyi Zhang, Yi Luo, Jean-Marie Lemercier, and Timo Gerkmann · 2021
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Sandglasset: a light multi-granularity self-attentive network for time-domain speech separation
Max WY Lam, Jun Wang, Dan Su, and Dong Yu · 2021
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Speechbrain: A general-purpose speech toolkit
Mirco Ravanelli, Titouan Parcollet, Peter Plantinga, Aku Rouhe, Samuele Cornell, Loren Lugosch, Cem Subakan, Nauman Dawalatabad, Abdelwahab Heba, Jianyuan Zhong, et al · 2021
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Attention is all you need in speech separation
Cem Subakan, Mirco Ravanelli, Samuele Cornell, Mirko Bronzi, and Jianyuan Zhong · 2021
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Convolutional neural networks with gated recurrent connections
Jianfeng Wang and Xiaolin Hu · 2021
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On the design and training strategies for rnn-based online neural speech separation systems
Kai Li and Yi Luo · 2022
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Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
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Stepwise-refining speech separation network via fine-grained encoding in high-order latent domain
Zengwei Yao, Wenjie Pei, Fanglin Chen, Guangming Lu, and David Zhang · 2022
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