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Tiago Falk

3 accepted papers

2026

DITSE: HIGH-FIDELITY GENERATIVE SPEECH ENHANCEMENT VIA LATENT DIFFUSION TRANSFORMERS

ICASSP 2026poster

Real-world speech recordings suffer from degradations such as background noise and reverberation. Speech enhancement aims to mitigate these issues by generating clean high-fidelity signals. While recent generative approaches for speech enhancement have shown promising results, they still face two ma…

Cited by 0SourcePDFScholar
2020

An end-to-end approach for the verification problem: learning the right distance

ICML 2020poster

In this contribution, we augment the metric learning setting by introducing a parametric pseudo-distance, trained jointly with the encoder. Several interpretations are thus drawn for the learned distance-like model’s output. We first show it approximates a likelihood ratio which can be used for hypo…

2019

Multi-objective training of Generative Adversarial Networks with multiple discriminators

ICML 2019oral

Recent literature has demonstrated promising results for training Generative Adversarial Networks by employing a set of discriminators, in contrast to the traditional game involving one generator against a single adversary. Such methods perform single-objective optimization on some simple consolidat…

Cited by 89SourcePDFScholar