etzinis/activelearning

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Python
License
MIT License
Created over 6 years ago
Updated over 6 years ago

etzinis/activelearning

etzinis

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Active Learning for Emotionally Salient Utterances and Segments using Text & Audio

sudo_rm_rf

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.

Jupyter Notebook

two_step_mask_learning

A two step optimization for sound source separation on the adaptive front-end domain

unsup_speech_enh_adaptation

Unsupervised domain adaptation for conversational speech enhancement using RemixIT

Jupyter Notebook

fedenhance

Code for the paper: Separate but togerher: Unsupervised Federated Learning for Speech Enhancement from non-iid data

Jupyter Notebook

heterogeneous_separation

Code and data recipes for the paper: Heterogeneous Target Speech Separation

unsupervised_spatial_dc

Code for the paper: "Unsupervised Deep Clustering for Source Separation: Direct Learning from Mixtures using Spatial Information"

biased_separation

Code for the paper: Unified Gradient Reweighting for Model Biasing with Applications to Source Separation

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 Roux

nldrp

Non linear dynamics for emotion classification

lathesis

Latex Code of thesis tools for manipulation

bootstrapped_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.

Jupyter Notebook

pat_rec_ntua

Labs exercises in NTUA (2016-2017) for the Pattern Recognition course 9th semester Contributors: Efthymios Tzinis Konstantinos Kallas