Shayan Gharib

According to our database, Shayan Gharib authored at least 10 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Adversarial Representation Learning for Robust Privacy Preservation in Audio.

Shayan Gharib, Minh Tran, Diep Luong, Konstantinos Drossos, Tuomas Virtanen

CoRR, 2023

Representation Learning for Audio Privacy Preservation Using Source Separation and Robust Adversarial Learning.

Diep Luong, Minh Tran, Shayan Gharib, Konstantinos Drossos, Tuomas Virtanen

Proceedings of the IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 2023

Extending Interpolation Consistency Training for Unsupervised Domain Adaptation.

Shayan Gharib, Arto Klami

Proceedings of the International Joint Conference on Neural Networks, 2023

2020

VOICe Dataset.

Shayan Gharib, Konstantinos Drossos, Eemi Fagerlund, Tuomas Virtanen

Dataset, January, 2020

Sound Event Detection with Depthwise Separable and Dilated Convolutions.

Konstantinos Drossos, Stylianos I. Mimilakis, Shayan Gharib, Yanxiong Li, Tuomas Virtanen

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2019

Code of the method presented in the paper: Drossos et al, "Language Modelling for Sound Event Detection with Teacher Forcing and Scheduled Sampling," in proceedings of DCASE 2019.

Konstantinos Drossos, Shayan Gharib, Paul Magron, Tuomas Virtanen

Dataset, November, 2019

VOICe: A Sound Event Detection Dataset For Generalizable Domain Adaptation.

Shayan Gharib, Konstantinos Drossos, Eemi Fagerlund, Tuomas Virtanen

CoRR, 2019

Language Modelling for Sound Event Detection with Teacher Forcing and Scheduled Sampling.

Konstantinos Drossos, Shayan Gharib, Paul Magron, Tuomas Virtanen

Proceedings of the Workshop on Detection and Classification of Acoustic Scenes and Events 2019 (DCASE 2019), 2019

2018

Acoustic Scene Classification: a Competition Review.

Shayan Gharib, Honain Derrar, Daisuke Niizumi, Tuukka Senttula, Janne Tommola, Toni Heittola, Tuomas Virtanen, Heikki Huttunen

Proceedings of the 28th IEEE International Workshop on Machine Learning for Signal Processing, 2018

Unsupervised adversarial domain adaptation for acoustic scene classification.

Shayan Gharib, Konstantinos Drossos, Emre Cakir, Dmitriy Serdyuk, Tuomas Virtanen

Proceedings of the Workshop on Detection and Classification of Acoustic Scenes and Events, 2018