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Code for SuDoRm-Rf networks for efficient audio source separation. SuDoRm-Rf stands for SUccessive DOwnsampling and Resampling of Multi-Resolution Features which enables a more efficient way of separating sources from mixtures.two_step_mask_learning
A two step optimization for sound source separation on the adaptive front-end domainunsup_speech_enh_adaptation
Unsupervised domain adaptation for conversational speech enhancement using RemixITfedenhance
Code for the paper: Separate but togerher: Unsupervised Federated Learning for Speech Enhancement from non-iid dataheterogeneous_separation
Code and data recipes for the paper: Heterogeneous Target Speech Separationunsupervised_spatial_dc
Code for the paper: "Unsupervised Deep Clustering for Source Separation: Direct Learning from Mixtures using Spatial Information"optimal_condition_training
Code and data recipes for the paper: Optimal Condition Training for Target Source Separation by Efthymios Tzinis, Gordon Wichern, Paris Smaragdis and Jonathan Le Rouxnldrp
Non linear dynamics for emotion classificationlathesis
Latex Code of thesis tools for manipulationactivelearning
Active Learning for Emotionally Salient Utterances and Segments using Text & Audiobootstrapped_mds
Bootstrapped MDS: A Coordinate Search Algorithm for Multidimensional Scaling which optimizes Stress by evaluating the function multiple times over different coordinates but also bootstraping over previous successful iterations. With this algorithm there is a probability of evaluating the function alongside a coordinate step depending on the previous successful evaluations across this coordinate.pat_rec_ntua
Labs exercises in NTUA (2016-2017) for the Pattern Recognition course 9th semester Contributors: Efthymios Tzinis Konstantinos KallasLove Open Source and this site? Check out how you can help us