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Researcher profile

Olivier Pietquin

6 papers in the PaperMetrix corpus

Publications

Papers by this author

  1. MultiVec: a Multilingual and Multilevel Representation Learning Toolkit for NLP

    2016

    We present MultiVec, a new toolkit for computing continuous representations for text at different granularity levels (word-level or sequences of words).MultiVec includes Mikolov et al. [2013b]'s word2vec features, Le and Mikolov [2014]'s paragraph vector (batch …

  2. End-to-End Automatic Speech Translation of Audiobooks

    2018

    We investigate end-to-end speech-to-text translation on a corpus of audiobooks specifically augmented for this task. Previous works investigated the extreme case where source language transcription is not available during learning nor decoding, but we also …

  3. End-to-end optimization of goal-driven and visually grounded dialogue systems

    2017 · arXiv (Cornell University)

    End-to-end design of dialogue systems has recently become a popular research topic thanks to powerful tools such as encoder-decoder architectures for sequence-to-sequence learning. Yet, most current approaches cast human-machine dialogue management as a supervised learning …

  4. Adversarially Guided Actor-Critic

    2021 · arXiv (Cornell University)

    Despite definite success in deep reinforcement learning problems,\nactor-critic algorithms are still confronted with sample inefficiency in\ncomplex environments, particularly in tasks where efficient exploration is a\nbottleneck. These methods consider a policy (the actor) and a value …

  5. Self-Imitation Advantage Learning

    2021

    Self-imitation learning is a Reinforcement Learning (RL) method that encourages actions whose returns were higher than expected, which helps in hard exploration and sparse reward problems. It was shown to improve the performance of on-policy …

  6. Listen and Translate: A Proof of Concept for End-to-End Speech-to-Text Translation

    2016 · arXiv (Cornell University)

    This paper proposes a first attempt to build an end-to-end speech-to-text translation system, which does not use source language transcription during learning or decoding. We propose a model for direct speech-to-text translation, which gives promising …