Ronan Collobert

research

∙ 05/19/2023

Unsupervised ASR via Cross-Lingual Pseudo-Labeling

Recent work has shown that it is possible to train an unsupervised autom...

0 Tatiana Likhomanenko, et al. ∙

research

∙ 11/11/2022

Continuous Soft Pseudo-Labeling in ASR

Continuous pseudo-labeling (PL) algorithms such as slimIPL have recently...

0 Tatiana Likhomanenko, et al. ∙

research

∙ 11/02/2022

More Speaking or More Speakers?

Self-training (ST) and self-supervised learning (SSL) methods have demon...

0 Dan Berrebbi, et al. ∙

research

∙ 10/17/2022

Continuous Pseudo-Labeling from the Start

Self-training (ST), or pseudo-labeling has sparked significant interest ...

0 Dan Berrebbi, et al. ∙

research

∙ 01/29/2022

Flashlight: Enabling Innovation in Tools for Machine Learning

As the computational requirements for machine learning systems and the s...

0 Jacob Kahn, et al. ∙

research

∙ 01/28/2022

Star Temporal Classification: Sequence Classification with Partially Labeled Data

We develop an algorithm which can learn from partially labeled and unseg...

0 Vineel Pratap, et al. ∙

research

∙ 10/30/2021

Pseudo-Labeling for Massively Multilingual Speech Recognition

Semi-supervised learning through pseudo-labeling has become a staple of ...

0 Loren Lugosch, et al. ∙

research

∙ 10/12/2021

Word Order Does Not Matter For Speech Recognition

In this paper, we study training of automatic speech recognition system ...

0 Vineel Pratap, et al. ∙

research

∙ 06/14/2021

Kaizen: Continuously improving teacher using Exponential Moving Average for semi-supervised speech recognition

In this paper, we introduce the Kaizen framework that uses a continuousl...

0 Vimal Manohar, et al. ∙

research

∙ 06/06/2021

CAPE: Encoding Relative Positions with Continuous Augmented Positional Embeddings

Without positional information, attention-based transformer neural netwo...

0 Tatiana Likhomanenko, et al. ∙

research

∙ 04/02/2021

Robust wav2vec 2.0: Analyzing Domain Shift in Self-Supervised Pre-Training

Self-supervised learning of speech representations has been a very activ...

0 Wei-Ning Hsu, et al. ∙

research

∙ 12/07/2020

MLS: A Large-Scale Multilingual Dataset for Speech Research

This paper introduces Multilingual LibriSpeech (MLS) dataset, a large mu...

0 Vineel Pratap, et al. ∙

research

∙ 10/30/2020

Joint Masked CPC and CTC Training for ASR

Self-supervised learning (SSL) has shown promise in learning representat...

0 Chaitanya Talnikar, et al. ∙

research

∙ 10/22/2020

Rethinking Evaluation in ASR: Are Our Models Robust Enough?

Is pushing numbers on a single benchmark valuable in automatic speech re...

0 Tatiana Likhomanenko, et al. ∙

research

∙ 10/22/2020

slimIPL: Language-Model-Free Iterative Pseudo-Labeling

Recent results in end-to-end ASR have demonstrated the efficacy of simpl...

0 Tatiana Likhomanenko, et al. ∙

research

∙ 10/22/2020

Self-training and Pre-training are Complementary for Speech Recognition

Self-training and unsupervised pre-training have emerged as effective ap...

0 Qiantong Xu, et al. ∙

research

∙ 07/06/2020

Massively Multilingual ASR: 50 Languages, 1 Model, 1 Billion Parameters

We study training a single acoustic model for multiple languages with th...

0 Vineel Pratap, et al. ∙

research

∙ 06/24/2020

Unsupervised Cross-lingual Representation Learning for Speech Recognition

This paper presents XLSR which learns cross-lingual speech representatio...

0 Alexis Conneau, et al. ∙

research

∙ 05/19/2020

Iterative Pseudo-Labeling for Speech Recognition

Pseudo-labeling has recently shown promise in end-to-end automatic speec...

0 Qiantong Xu, et al. ∙

research

∙ 05/01/2020

Multi-scale Transformer Language Models

We investigate multi-scale transformer language models that learn repres...

0 Sandeep Subramanian, et al. ∙

research

∙ 01/27/2020

Scaling Up Online Speech Recognition Using ConvNets

We design an online end-to-end speech recognition system based on Time-D...

0 Vineel Pratap, et al. ∙

research

∙ 12/17/2019

Libri-Light: A Benchmark for ASR with Limited or No Supervision

We introduce a new collection of spoken English audio suitable for train...

0 Jacob Kahn, et al. ∙

research

∙ 11/19/2019

End-to-end ASR: from Supervised to Semi-Supervised Learning with Modern Architectures

We study ResNet-, Time-Depth Separable ConvNets-, and Transformer-based ...

0 Gabriel Synnaeve, et al. ∙

research

∙ 06/10/2019

Word-level Speech Recognition with a Dynamic Lexicon

We propose a direct-to-word sequence model with a dynamic lexicon. Our w...

0 Ronan Collobert, et al. ∙

research

∙ 04/11/2019

wav2vec: Unsupervised Pre-training for Speech Recognition

We explore unsupervised pre-training for speech recognition by learning ...

0 Steffen Schneider, et al. ∙

research

∙ 04/09/2019

Who Needs Words? Lexicon-Free Speech Recognition

Lexicon-free speech recognition naturally deals with the problem of out-...

0 Tatiana Likhomanenko, et al. ∙

research

∙ 04/04/2019

Sequence-to-Sequence Speech Recognition with Time-Depth Separable Convolutions

We propose a fully convolutional sequence-to-sequence encoder architectu...

0 Awni Hannun, et al. ∙

research

∙ 02/16/2019

A Fully Differentiable Beam Search Decoder

We introduce a new beam search decoder that is fully differentiable, mak...

0 Ronan Collobert, et al. ∙

research

∙ 12/18/2018

wav2letter++: The Fastest Open-source Speech Recognition System

This paper introduces wav2letter++, the fastest open-source deep learnin...

0 Vineel Pratap, et al. ∙

research

∙ 12/17/2018

Fully Convolutional Speech Recognition

Current state-of-the-art speech recognition systems build on recurrent n...

0 Neil Zeghidour, et al. ∙

research

∙ 12/09/2018

To Reverse the Gradient or Not: An Empirical Comparison of Adversarial and Multi-task Learning in Speech Recognition

Transcribed datasets typically contain speaker identity for each instanc...

14 Yossi Adi, et al. ∙

research

∙ 06/19/2018

End-to-End Speech Recognition From the Raw Waveform

State-of-the-art speech recognition systems rely on fixed, hand-crafted ...

0 Neil Zeghidour, et al. ∙

research

∙ 12/22/2017

Letter-Based Speech Recognition with Gated ConvNets

In this paper we introduce a new speech recognition system, leveraging a...

0 Vitaliy Liptchinsky, et al. ∙

research

∙ 09/11/2016

Wav2Letter: an End-to-End ConvNet-based Speech Recognition System

This paper presents a simple end-to-end model for speech recognition, co...

0 Ronan Collobert, et al. ∙

research

∙ 06/30/2016

Neural Network-based Word Alignment through Score Aggregation

We present a simple neural network for word alignment that builds source...

0 Joël Legrand, et al. ∙

research

∙ 03/29/2016

Learning to Refine Object Segments

Object segmentation requires both object-level information and low-level...

0 Pedro O. Pinheiro, et al. ∙

research

∙ 11/12/2015

ProNet: Learning to Propose Object-specific Boxes for Cascaded Neural Networks

This paper aims to classify and locate objects accurately and efficientl...

0 Chen Sun, et al. ∙

research

∙ 06/20/2015

Learning to Segment Object Candidates

Recent object detection systems rely on two critical steps: (1) a set of...

0 Pedro O. Pinheiro, et al. ∙

research

∙ 06/18/2015

"The Sum of Its Parts": Joint Learning of Word and Phrase Representations with Autoencoders

Recently, there has been a lot of effort to represent words in continuou...

0 Rémi Lebret, et al. ∙

research

∙ 02/12/2015

Phrase-based Image Captioning

Generating a novel textual description of an image is an interesting pro...

0 Rémi Lebret, et al. ∙

research

∙ 12/29/2014

Simple Image Description Generator via a Linear Phrase-Based Approach

Generating a novel textual description of an image is an interesting pro...

0 Rémi Lebret, et al. ∙

research

∙ 12/22/2014

Learning linearly separable features for speech recognition using convolutional neural networks

Automatic speech recognition systems usually rely on spectral-based feat...

0 Dimitri Palaz, et al. ∙

research

∙ 12/22/2014

Joint RNN-Based Greedy Parsing and Word Composition

This paper introduces a greedy parser based on neural networks, which le...

0 Joël Legrand, et al. ∙

research

∙ 12/20/2014

Video (language) modeling: a baseline for generative models of natural videos

We propose a strong baseline model for unsupervised feature learning usi...

0 MarcAurelio Ranzato, et al. ∙

research

∙ 12/19/2014

N-gram-Based Low-Dimensional Representation for Document Classification

The bag-of-words (BOW) model is the common approach for classifying docu...

0 Rémi Lebret, et al. ∙

research

∙ 12/16/2014

Rehabilitation of Count-based Models for Word Vector Representations

Recent works on word representations mostly rely on predictive models. D...

0 Rémi Lebret, et al. ∙

research

∙ 11/23/2014

From Image-level to Pixel-level Labeling with Convolutional Networks

We are interested in inferring object segmentation by leveraging only ob...

0 Pedro O. Pinheiro, et al. ∙

research

∙ 12/07/2013

End-to-end Phoneme Sequence Recognition using Convolutional Neural Networks

Most phoneme recognition state-of-the-art systems rely on a classical ne...

0 Dimitri Palaz, et al. ∙

research

∙ 06/12/2013

Recurrent Convolutional Neural Networks for Scene Parsing

Scene parsing is a technique that consist on giving a label to all pixel...

0 Pedro H. O. Pinheiro, et al. ∙

research

∙ 04/03/2013

Estimating Phoneme Class Conditional Probabilities from Raw Speech Signal using Convolutional Neural Networks

In hybrid hidden Markov model/artificial neural networks (HMM/ANN) autom...

0 Dimitri Palaz, et al. ∙

Ronan Collobert

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