Compute and Memory Efficient Universal Sound Source Separation

[1]  Yi Luo,et al.  Ultra-Lightweight Speech Separation Via Group Communication , 2020, ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[2]  Justin Salamon,et al.  What’s all the Fuss about Free Universal Sound Separation Data? , 2020, ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[3]  Mirco Ravanelli,et al.  Attention Is All You Need In Speech Separation , 2020, ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[4]  Romain Hennequin,et al.  Spleeter: a fast and efficient music source separation tool with pre-trained models , 2020, J. Open Source Softw..

[5]  Gabriel Synnaeve,et al.  Real Time Speech Enhancement in the Waveform Domain , 2020, INTERSPEECH.

[6]  Cumhur Erkut,et al.  Hydranet: A Real-Time Waveform Separation Network , 2020, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[7]  C. Rascón,et al.  Lightweight Online Separation of the Sound Source of Interest through BLSTM-Based Binary Masking , 2020, Computación y Sistemas.

[8]  Neil Zeghidour,et al.  Wavesplit: End-to-End Speech Separation by Speaker Clustering , 2020, IEEE/ACM Transactions on Audio, Speech, and Language Processing.

[9]  Natalia Gimelshein,et al.  PyTorch: An Imperative Style, High-Performance Deep Learning Library , 2019, NeurIPS.

[10]  Efthymios Tzinis,et al.  Improving Universal Sound Separation Using Sound Classification , 2019, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[11]  Roger Wattenhofer,et al.  Monaural Music Source Separation using a ResNet Latent Separator Network , 2019, 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI).

[12]  P. Smaragdis,et al.  Two-Step Sound Source Separation: Training On Learned Latent Targets , 2019, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[13]  T. Yoshioka,et al.  Dual-Path RNN: Efficient Long Sequence Modeling for Time-Domain Single-Channel Speech Separation , 2019, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[14]  Francis Bach,et al.  Music Source Separation in the Waveform Domain , 2019, ArXiv.

[15]  Chuang Gan,et al.  Once for All: Train One Network and Specialize it for Efficient Deployment , 2019, ICLR.

[16]  DeLiang Wang,et al.  TCNN: Temporal Convolutional Neural Network for Real-time Speech Enhancement in the Time Domain , 2019, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[17]  Jonathan Le Roux,et al.  Universal Sound Separation , 2019, 2019 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA).

[18]  DeLiang Wang,et al.  Divide and Conquer: A Deep CASA Approach to Talker-Independent Monaural Speaker Separation , 2019, IEEE/ACM Transactions on Audio, Speech, and Language Processing.

[19]  Ning Xu,et al.  Slimmable Neural Networks , 2018, ICLR.

[20]  Linda G. Shapiro,et al.  ESPNetv2: A Light-Weight, Power Efficient, and General Purpose Convolutional Neural Network , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[21]  Scott Wisdom,et al.  Differentiable Consistency Constraints for Improved Deep Speech Enhancement , 2018, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[22]  Jonathan Le Roux,et al.  SDR – Half-baked or Well Done? , 2018, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[23]  Nima Mesgarani,et al.  Conv-TasNet: Surpassing Ideal Time–Frequency Magnitude Masking for Speech Separation , 2018, IEEE/ACM Transactions on Audio, Speech, and Language Processing.

[24]  Gregory Shakhnarovich,et al.  Deep Back-Projection Networks for Super-Resolution , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[25]  Ashish Vaswani,et al.  Self-Attention with Relative Position Representations , 2018, NAACL.

[26]  Erich Elsen,et al.  Efficient Neural Audio Synthesis , 2018, ICML.

[27]  Bo Chen,et al.  MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications , 2017, ArXiv.

[28]  Raquel Urtasun,et al.  Understanding the Effective Receptive Field in Deep Convolutional Neural Networks , 2016, NIPS.

[29]  François Chollet,et al.  Xception: Deep Learning with Depthwise Separable Convolutions , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[30]  Geoffrey E. Hinton,et al.  Layer Normalization , 2016, ArXiv.

[31]  Jesper Jensen,et al.  Permutation invariant training of deep models for speaker-independent multi-talker speech separation , 2016, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[32]  Nicholas D. Lane,et al.  DeepX: A Software Accelerator for Low-Power Deep Learning Inference on Mobile Devices , 2016, 2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN).

[33]  Karol J. Piczak.  ESC: Dataset for Environmental Sound Classification , 2015, ACM Multimedia.

[34]  Zhuo Chen,et al.  Deep clustering: Discriminative embeddings for segmentation and separation , 2015, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[35]  Thomas Brox,et al.  U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.

[36]  Jian Sun,et al.  Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[37]  Jimmy Ba,et al.  Adam: A Method for Stochastic Optimization , 2014, ICLR.

[38]  Paris Smaragdis,et al.  Deep learning for monaural speech separation , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[39]  Andrew Zisserman,et al.  Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps , 2013, ICLR.

[40]  Rémi Gribonval,et al.  Performance measurement in blind audio source separation , 2006, IEEE Transactions on Audio, Speech, and Language Processing.

[41]  Janet M. Baker,et al.  The Design for the Wall Street Journal-based CSR Corpus , 1992, HLT.

[42]  Paris Smaragdis,et al.  Efficient Source Separation Using Bitwise Neural Networks , 2018 .