[1] C. E. Cherry, "Some Experiments on the Recognition of Speech, with One and with Two Ears," Journal of the Acoustical Society of America, vol. 25, no. 5, pp. 975-979, 1953.
[2] J. H. McDermott, “The Cocktail Party Problem,” Current Biology, vol. 19, no. 22, pp. 1024–1027, 2009.
[3] D. Wang and J. Chen, "Supervised Speech Separation Based on Deep Learning: An Overview," IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 26, no. 10, pp. 1702-1726, 2018.
[4] J. R. Hershey, Z. Chen, J. Le Roux, and S. Watanabe, "Deep Clustering: Discriminative Embeddings for Segmentation and Separation," in Proc. ICASSP, 2016, pp. 31-35.
[5] M. Kolbæk, D. Yu, Z.-H. Tan, and J. Jensen, "Multitalker Speech Separation with Utterance-Level Permutation Invariant Training of Deep Recurrent Neural Networks," IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 25, no. 10, pp. 1901-1913, 2017.
[6] Y. Luo, Z. Chen, and N. Mesgarani, "Speaker-Independent Speech Separation with Deep Attractor Network," IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 26, no. 4, pp. 787-796, 2018.
[7] Z.-Q. Wang and D. Wang, "Combining Spectral and Spatial Features for Deep Learning Based Blind Speaker Separation," IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 27, no. 2, pp. 457-468, 2019.
[8] A. Ephrat, I. Mosseri, O. Lang, T. Dekel, K. Wilson, A. Hassidim, W. T. Freeman, and M. Rubinstein, "Looking to Listen at the Cocktail Party: A Speaker-Independent Audio-Visual Model for Speech Separation," ACM Transactions on Graphics, vol. 37, no. 4, 2018.
[9] Y. Liu and D. Wang, "Divide and Conquer: A Deep CASA Approach to Talker-Independent Monaural Speaker Separation," IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 27, no. 12, pp. 2092-2102, 2019.
[10] Y. Luo and N. Mesgarani, "Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation," IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 27, no. 8, pp. 1256-1266, 2019.
[11] Z.-Q. Wang, K. Tan, and D. Wang, "Deep Learning Based Phase Reconstruction for Speaker Separation: A Trigonometric Perspective," in Proc. ICASSP, 2019, pp. 71-75.
[12] K. Žmolíková, M. Delcroix, K. Kinoshita, T. Ochiai, T. Nakatani, L. Burget, and J. Černocký, “Speaker-Beam: Speaker Aware Neural Network for Target Speaker Extraction in Speech Mixtures,” IEEE Journal of Selected Topics in Signal Processing, vol. 13, no. 4, pp. 800–814, 2019.
[13] I. Kavalerov, S. Wisdom, H. Erdogan, B. Patton, K. Wilson, J. Le Roux, and J. R. Hershey, “Universal Sound Separation,” in Proc. WASPAA, 2019, pp. 175–179.
[14] D. Yin, C. Luo, Z. Xiong, and W. Zeng, “PHASEN: A Phase-and-Harmonics-Aware Speech Enhancement Network,” in Proc. AAAI, 2020, pp. 9458–9465.
[15] Y. Xu, M. Yu, S.-X. Zhang, L. Chen, C. Weng, J. Liu, and D. Yu, "Neural Spatio-Temporal Beamformer for Target Speech Separation," in Proc. Interspeech, 2020, pp. 56-60.
[16] T. Jenrungrot, V. Jayaram, S. Seitz, and I. Kemelmacher-Shlizerman, "The Cone of Silence: Speech Separation by Localization," in Proc. NeurIPS, 2020.
[17] C. Tang, C. Luo, Z. Zhao, W. Xie, and W. Zeng, "Joint Time-Frequency and Time Domain Learning for Speech Enhancement," in Proc. IJCAI, 2020, pp. 3816-3822.
[18] E. Nachmani, Y. Adi, and L. Wolf, "Voice Separation with An Unknown Number of Multiple Speakers," in Proc. ICML, 2020, pp. 7121-7132.
[19] N. Zeghidour and D. Grangier, "Wavesplit: End-to-End Speech Separation by Speaker Clustering," IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 29, pp. 2840–2849, 2021.
[20] Z. Chen, T. Yoshioka, L. Lu, T. Zhou, Z. Meng, Y. Luo, J. Wu, X. Xiao, and J. Li, "Continuous Speech Separation: Dataset and Analysis," in Proc. ICASSP, 2020, pp. 7284-7288.
[21] Z. Zhang, Y. Xu, M. Yu, S. X. Zhang, L. Chen, D. S. Williamson, and D. Yu, "Multi-Channel Multi-Frame ADL-MVDR for Target Speech Separation," IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 29, pp. 3526-3540, 2021.