This repository contains papers for pure speech separation and multimodal speech separation.
✔️ [Joint Optimization of Masks and Deep Recurrent Neural Networks for Monaural Source Separation, Po-Sen Huang, TASLP 2015] [Paper] [Code (posenhuang)]
✔️ [Complex Ratio Masking for Monaural Speech Separation, DS Williamson, TASLP 2015] [Paper]
✔️ [Deep clustering: Discriminative embeddings for segmentation and separation, JR Hershey, ICASSP 2016] [Paper] [Code (Kai Li)] [Code (funcwj)]
✔️ [Single-channel multi-speaker separation using deep clustering, Y Isik, Interspeech 2016] [Paper] [Code (Kai Li)] [Code (funcwj)]
✔️ [Permutation invariant training of deep models for speaker-independent multi-talker speech separation, Dong Yu, ICASSP 2017] [Paper] [Code (Kai Li)]
✔️ [Recognizing Multi-talker Speech with Permutation Invariant Training, Dong Yu, ICASSP 2017] [Paper]
✔️ [Multitalker speech separation with utterance-level permutation invariant training of deep recurrent neural networks, M Kolbæk, TASLP 2017] [Paper] [Code (Kai Li)]
✔️ [Deep attractor network for single-microphone speaker separation, Zhuo Chen, ICASSP 2017] [Paper] [Code (Kai Li)]
✔️ [Alternative Objective Functions for Deep Clustering, Zhong-Qiu Wang, ICASSP 2018] [Paper]
✔️ [Speaker-independent Speech Separation with Deep Attractor Network, Luo Yi, TASLP 2018] [Paper] [Code (Kai Li)]
✔️ [Tasnet: time-domain audio separation network for real-time, single-channel speech separation, Luo Yi, ICASSP 2018] [Paper] [Code (Kai Li)]
✔️ [Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation, Luo Yi, TASLP 2019] [Paper] [Code (Kai Li)]
✔️ [Divide and Conquer: A Deep CASA Approach to Talker-independent Monaural Speaker Separation, Yuzhou Liu, TASLP 2019] [Paper] [Code]
✔️ [Dual-path RNN: efficient long sequence modeling for time-domain single-channel speech separation, Luo Yi, Arxiv 2019] [Paper] [Code (Kai Li)]
✔️ [End-to-end Microphone Permutation and Number Invariant Multi-channel Speech Separation, Luo Yi, Arxiv 2019] [Paper] [Code]
✔️ [FurcaNeXt: End-to-end monaural speech separation with dynamic gated dilated temporal convolutional networks, Liwen Zhang, MMM 2020] [Paper]
✔️ [Voice Separation with an Unknown Number of Multiple Speakers, Eliya Nachmani, Arxiv 2020] [Paper] [Demo]
✔️ [AN EMPIRICAL STUDY OF CONV-TASNET, Berkan Kadıoglu , Arxiv 2020] [Paper]
✔️ [Supervised Speech Separation Based on Deep Learning An Overview,DeLiang Wang, Arxiv 2018] [Paper]
✔️ [An Overview of Lead and Accompaniment Separation in Music, Arxiv 2018] [Paper]
✔️ [A consolidated perspective on multi-microphone speech enhancement and source separation, Arxiv 2017] [Paper]
✔️ [Audio-Visual Speech Enhancement Using Multimodal Deep Convolutional Neural Networks, Jen-Cheng Hou, TETCI 2017] [Paper] [Code]
✔️ [The Conversation: Deep Audio-Visual Speech Enhancement, Triantafyllos Afouras, Interspeech 2018] [Paper]
✔️ [End-to-end audiovisual speech recognition, Stavros Petridis, ICASSP 2018] [Paper] [Code]
✔️ [The Sound of Pixels, Hang Zhao, ECCV 2018] [Paper] [Code]
✔️ [Looking to Listen at the Cocktail Party: A Speaker-Independent Audio-Visual Model for Speech Separation, ARIEL EPHRAT, ACM Transactions on Graphics 2018] [Paper] [Code]
✔️ [Learning to Separate Object Sounds by Watching Unlabeled Video, Ruohan Gao, ECCV 2018] [Paper]
✔️ [Time domain audio visual speech separation, Jian Wu, Arxiv 2019] [Paper]
✔️ [Audio-Visual Speech Separation and Dereverberation with a Two-Stage Multimodal Network, Ke Tan, Arxiv 2019] [Paper]
✔️ [Co-Separating Sounds of Visual Objects, Ruohan Gao, ICCV 2019] [Paper] [Code]
I may not be able to get all the articles completely. So if you have an excellent essay or tutorial, you can update it in my format. At the same time, if you think the repository meets your needs, please give a star or fork, thank you.