Search Results for author: Philemon Brakel

Found 13 papers, 6 papers with code

Learning Coordinated Terrain-Adaptive Locomotion by Imitating a Centroidal Dynamics Planner

no code implementations30 Oct 2021 Philemon Brakel, Steven Bohez, Leonard Hasenclever, Nicolas Heess, Konstantinos Bousmalis

Imitation learning circumvents this problem and has been used with motion capture data to extract quadruped gaits for flat terrains.

Imitation Learning

Explicit Pareto Front Optimization for Constrained Reinforcement Learning

no code implementations1 Jan 2021 Sandy Huang, Abbas Abdolmaleki, Philemon Brakel, Steven Bohez, Nicolas Heess, Martin Riedmiller, Raia Hadsell

We propose a framework that uses a multi-objective RL algorithm to find a Pareto front of policies that trades off between the reward and constraint(s), and simultaneously searches along this front for constraint-satisfying policies.

Continuous Control reinforcement-learning

Light Gated Recurrent Units for Speech Recognition

1 code implementation26 Mar 2018 Mirco Ravanelli, Philemon Brakel, Maurizio Omologo, Yoshua Bengio

A field that has directly benefited from the recent advances in deep learning is Automatic Speech Recognition (ASR).

Automatic Speech Recognition speech-recognition

Learning Independent Features with Adversarial Nets for Non-linear ICA

1 code implementation ICLR 2018 Philemon Brakel, Yoshua Bengio

We propose to learn independent features with adversarial objectives which optimize such measures implicitly.

Improving speech recognition by revising gated recurrent units

1 code implementation29 Sep 2017 Mirco Ravanelli, Philemon Brakel, Maurizio Omologo, Yoshua Bengio

First, we suggest to remove the reset gate in the GRU design, resulting in a more efficient single-gate architecture.

speech-recognition Speech Recognition

A network of deep neural networks for distant speech recognition

no code implementations23 Mar 2017 Mirco Ravanelli, Philemon Brakel, Maurizio Omologo, Yoshua Bengio

Despite the remarkable progress recently made in distant speech recognition, state-of-the-art technology still suffers from a lack of robustness, especially when adverse acoustic conditions characterized by non-stationary noises and reverberation are met.

Distant Speech Recognition Speech Enhancement +1

Towards End-to-End Speech Recognition with Deep Convolutional Neural Networks

1 code implementation10 Jan 2017 Ying Zhang, Mohammad Pezeshki, Philemon Brakel, Saizheng Zhang, Cesar Laurent Yoshua Bengio, Aaron Courville

Meanwhile, Connectionist Temporal Classification (CTC) with Recurrent Neural Networks (RNNs), which is proposed for labeling unsegmented sequences, makes it feasible to train an end-to-end speech recognition system instead of hybrid settings.

Automatic Speech Recognition speech-recognition

Deconstructing the Ladder Network Architecture

no code implementations19 Nov 2015 Mohammad Pezeshki, Linxi Fan, Philemon Brakel, Aaron Courville, Yoshua Bengio

Although the empirical results are impressive, the Ladder Network has many components intertwined, whose contributions are not obvious in such a complex architecture.

Denoising

End-to-End Attention-based Large Vocabulary Speech Recognition

1 code implementation18 Aug 2015 Dzmitry Bahdanau, Jan Chorowski, Dmitriy Serdyuk, Philemon Brakel, Yoshua Bengio

Many of the current state-of-the-art Large Vocabulary Continuous Speech Recognition Systems (LVCSR) are hybrids of neural networks and Hidden Markov Models (HMMs).

Acoustic Modelling speech-recognition +1

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