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07/25/2023
How to Scale Your EMA
Preserving training dynamics across batch sizes is an important tool for...
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06/13/2023
VISION Datasets: A Benchmark for Vision-based InduStrial InspectiON
Despite progress in vision-based inspection algorithms, real-world indus...
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05/19/2023
Unsupervised ASR via Cross-Lingual Pseudo-Labeling
Recent work has shown that it is possible to train an unsupervised autom...
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03/11/2023
Stabilizing Transformer Training by Preventing Attention Entropy Collapse
Training stability is of great importance to Transformers. In this work,...
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12/20/2022
Joint Speech Transcription and Translation: Pseudo-Labeling with Out-of-Distribution Data
Self-training has been shown to be helpful in addressing data scarcity f...
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11/11/2022
Continuous Soft Pseudo-Labeling in ASR
Continuous pseudo-labeling (PL) algorithms such as slimIPL have recently...
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11/02/2022
More Speaking or More Speakers?
Self-training (ST) and self-supervised learning (SSL) methods have demon...
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10/17/2022
Continuous Pseudo-Labeling from the Start
Self-training (ST), or pseudo-labeling has sparked significant interest ...
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07/15/2022
Position Prediction as an Effective Pretraining Strategy
Transformers have gained increasing popularity in a wide range of applic...
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01/29/2022
Flashlight: Enabling Innovation in Tools for Machine Learning
As the computational requirements for machine learning systems and the s...
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10/30/2021
Pseudo-Labeling for Massively Multilingual Speech Recognition
Semi-supervised learning through pseudo-labeling has become a staple of ...
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10/12/2021
Word Order Does Not Matter For Speech Recognition
In this paper, we study training of automatic speech recognition system ...
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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...
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06/06/2021
CAPE: Encoding Relative Positions with Continuous Augmented Positional Embeddings
Without positional information, attention-based transformer neural netwo...
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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...
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10/30/2020
Joint Masked CPC and CTC Training for ASR
Self-supervised learning (SSL) has shown promise in learning representat...
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10/22/2020
Rethinking Evaluation in ASR: Are Our Models Robust Enough?
Is pushing numbers on a single benchmark valuable in automatic speech re...
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10/22/2020
slimIPL: Language-Model-Free Iterative Pseudo-Labeling
Recent results in end-to-end ASR have demonstrated the efficacy of simpl...
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10/22/2020
Self-training and Pre-training are Complementary for Speech Recognition
Self-training and unsupervised pre-training have emerged as effective ap...
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05/19/2020
Iterative Pseudo-Labeling for Speech Recognition
Pseudo-labeling has recently shown promise in end-to-end automatic speec...
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01/27/2020
Scaling Up Online Speech Recognition Using ConvNets
We design an online end-to-end speech recognition system based on Time-D...
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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...
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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 ...
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04/09/2019
Who Needs Words? Lexicon-Free Speech Recognition
Lexicon-free speech recognition naturally deals with the problem of out-...
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06/04/2017
InfiniteBoost: building infinite ensembles with gradient descent
In machine learning ensemble methods have demonstrated high accuracy for...
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05/24/2017
