Search Results for author: Joao Monteiro

Found 10 papers, 3 papers with code

Monotonicity as a requirement and as a regularizer: efficient methods and applications

no code implementations29 Sep 2021 Joao Monteiro, Mohamed Osama Ahmed, Hossein Hajimirsadeghi, Greg Mori

We study the setting where risk minimization is performed over general classes of models and consider two cases where monotonicity is treated as either a requirement to be satisfied everywhere or a useful property.

Image Classification

Domain Conditional Predictors for Domain Adaptation

no code implementations25 Jun 2021 Joao Monteiro, Xavier Gibert, Jianqiao Feng, Vincent Dumoulin, Dar-Shyang Lee

Domain adaptation approaches thus appeared as a useful framework yielding extra flexibility in that distinct train and test data distributions are supported, provided that other assumptions are satisfied such as covariate shift, which expects the conditional distributions over labels to be independent of the underlying data distribution.

Domain Adaptation

Learning Semantic Similarities for Prototypical Classifiers

no code implementations1 Jan 2021 Joao Monteiro, Isabela Albuquerque, Jahangir Alam, Tiago Falk

Recent metric learning approaches parametrize semantic similarity measures through the use of an encoder trained along with a similarity model, which operates over pairs of representations.

Few-Shot Learning Metric Learning +4

On The Performance of Time-Pooling Strategies for End-to-End Spoken Language Identification

no code implementations LREC 2020 Joao Monteiro, Md Jahangir Alam, Tiago Falk

Automatic speech processing applications often have to deal with the problem of aggregating local descriptors (i. e., representations of input speech data corresponding to specific portions across the time dimension) and turning them into a single fixed-dimension representation, known as global descriptor, on top of which downstream classification tasks can be performed.

Language Identification Representation Learning +1

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

1 code implementation ICML 2020 Joao Monteiro, Isabela Albuquerque, Jahangir Alam, R. Devon Hjelm, Tiago Falk

In this contribution, we augment the metric learning setting by introducing a parametric pseudo-distance, trained jointly with the encoder.

Metric Learning

Multi-task self-supervised learning for Robust Speech Recognition

1 code implementation25 Jan 2020 Mirco Ravanelli, Jianyuan Zhong, Santiago Pascual, Pawel Swietojanski, Joao Monteiro, Jan Trmal, Yoshua Bengio

We then propose a revised encoder that better learns short- and long-term speech dynamics with an efficient combination of recurrent and convolutional networks.

Robust Speech Recognition Self-Supervised Learning

A Simplified Fully Quantized Transformer for End-to-end Speech Recognition

no code implementations9 Nov 2019 Alex Bie, Bharat Venkitesh, Joao Monteiro, Md. Akmal Haidar, Mehdi Rezagholizadeh

While significant improvements have been made in recent years in terms of end-to-end automatic speech recognition (ASR) performance, such improvements were obtained through the use of very large neural networks, unfit for embedded use on edge devices.

Automatic Speech Recognition

Generative Adversarial Speaker Embedding Networks for Domain Robust End-to-End Speaker Verification

no code implementations7 Nov 2018 Gautam Bhattacharya, Joao Monteiro, Jahangir Alam, Patrick Kenny

Furthermore, we are able to significantly boost verification performance by averaging our different GAN models at the score level, achieving a relative improvement of 7. 2% over the baseline.

Dimensionality Reduction Speaker Verification

On-line Adaptative Curriculum Learning for GANs

3 code implementations31 Jul 2018 Thang Doan, Joao Monteiro, Isabela Albuquerque, Bogdan Mazoure, Audrey Durand, Joelle Pineau, R. Devon Hjelm

We argue that less expressive discriminators are smoother and have a general coarse grained view of the modes map, which enforces the generator to cover a wide portion of the data distribution support.

Multi-Armed Bandits Stochastic Optimization

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