Self-supervised learning for time series analysis: Taxonomy, progress, and prospects

K Zhang, Q Wen, C Zhang, R Cai, M **… - … on Pattern Analysis …, 2024 - ieeexplore.ieee.org
Self-supervised learning (SSL) has recently achieved impressive performance on various
time series tasks. The most prominent advantage of SSL is that it reduces the dependence …

Automated medical coding on MIMIC-III and MIMIC-IV: a critical review and replicability study

J Edin, A Junge, JD Havtorn, L Borgholt… - Proceedings of the 46th …, 2023 - dl.acm.org
Medical coding is the task of assigning medical codes to clinical free-text documentation.
Healthcare professionals manually assign such codes to track patient diagnoses and …

Mavil: Masked audio-video learners

PY Huang, V Sharma, H Xu, C Ryali… - Advances in …, 2023 - proceedings.neurips.cc
Abstract We present Masked Audio-Video Learners (MAViL) to learn audio-visual
representations with three complementary forms of self-supervision:(1) reconstructing …

Comparative layer-wise analysis of self-supervised speech models

A Pasad, B Shi, K Livescu - ICASSP 2023-2023 IEEE …, 2023 - ieeexplore.ieee.org
Many self-supervised speech models, varying in their pre-training objective, input modality,
and pre-training data, have been proposed in the last few years. Despite impressive …

Ml-superb: Multilingual speech universal performance benchmark

J Shi, D Berrebbi, W Chen, HL Chung, EP Hu… - arxiv preprint arxiv …, 2023 - arxiv.org
Speech processing Universal PERformance Benchmark (SUPERB) is a leaderboard to
benchmark the performance of Self-Supervised Learning (SSL) models on various speech …

Exploration of efficient end-to-end asr using discretized input from self-supervised learning

X Chang, B Yan, Y Fujita, T Maekaku… - arxiv preprint arxiv …, 2023 - arxiv.org
Self-supervised learning (SSL) of speech has shown impressive results in speech-related
tasks, particularly in automatic speech recognition (ASR). While most methods employ the …

[PDF][PDF] A path towards autonomous machine intelligence version 0.9. 2, 2022-06-27

Y LeCun - Open Review, 2022 - openreview.net
How could machines learn as efficiently as humans and animals? How could machines
learn to reason and plan? How could machines learn representations of percepts and action …

Dphubert: Joint distillation and pruning of self-supervised speech models

Y Peng, Y Sudo, S Muhammad, S Watanabe - arxiv preprint arxiv …, 2023 - arxiv.org
Self-supervised learning (SSL) has achieved notable success in many speech processing
tasks, but the large model size and heavy computational cost hinder the deployment …

Dinosr: Self-distillation and online clustering for self-supervised speech representation learning

AH Liu, HJ Chang, M Auli, WN Hsu… - Advances in Neural …, 2023 - proceedings.neurips.cc
In this paper, we introduce self-distillation and online clustering for self-supervised speech
representation learning (DinoSR) which combines masked language modeling, self …

Reproducing whisper-style training using an open-source toolkit and publicly available data

Y Peng, J Tian, B Yan, D Berrebbi… - 2023 IEEE Automatic …, 2023 - ieeexplore.ieee.org
Pre-training speech models on large volumes of data has achieved remarkable success.
OpenAI Whisper is a multilingual multitask model trained on 680k hours of supervised …