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A neural network alternative to non-negative audio models., and . ICASSP, page 86-90. IEEE, (2017)A Style Transfer Approach to Source Separation., , and . WASPAA, page 170-174. IEEE, (2019)AutoDub: Automatic Redubbing for Voiceover Editing., , and . UIST, page 533-538. ACM, (2017)Personalized PercepNet: Real-Time, Low-Complexity Target Voice Separation and Enhancement., , , , and . Interspeech, page 1124-1128. ISCA, (2021)Neural network alternatives toconvolutive audio models for source separation., , and . MLSP, page 1-6. IEEE, (2017)End-To-End Source Separation With Adaptive Front-Ends., , and . ACSSC, page 684-688. IEEE, (2018)Performance Based Cost Functions for End-to-End Speech Separation., , and . APSIPA, page 350-355. IEEE, (2018)Two-Step Sound Source Separation: Training On Learned Latent Targets., , , , and . ICASSP, page 31-35. IEEE, (2020)Vocal Separation using Singer-Vowel Priors Obtained from Polyphonic Audio., , , and . ISMIR, page 283-288. (2014)End-to-end non-negative auto-encoders: a deep neural alternative to non-negative audio modeling. University of Illinois Urbana-Champaign, USA, (2020)