Match to Win: Analysing Sequences Lengths for Efficient Self-supervised
Learning in Speech and Audio

Match to Win: Analysing Sequences Lengths for Efficient Self-supervised Learning in Speech and Audio

30 September 2022

Javier Fernandez-Marques

Titouan Parcollet

Pedro Porto Buarque de Gusmão

Nicholas D. Lane

Papers citing "Match to Win: Analysing Sequences Lengths for Efficient Self-supervised Learning in Speech and Audio"

8 / 8 papers shown

Title
Efficient Training of Self-Supervised Speech Foundation Models on a Compute Budget Andy T. Liu Yi-Cheng Lin Haibin Wu Stefan Winkler Hung-yi Lee 25 1 0 09 Sep 2024
Sustainable self-supervised learning for speech representations Luis Lugo Valentin Vielzeuf 29 2 0 11 Jun 2024
AudioRepInceptionNeXt: A lightweight single-stream architecture for efficient audio recognition Kin Wai Lau Yasar Abbas Ur Rehman L. Po 19 1 0 21 Apr 2024
Training Machine Learning models at the Edge: A Survey Aymen Rayane Khouas Mohamed Reda Bouadjenek Hakim Hacid Sunil Aryal 24 9 0 05 Mar 2024
Efficiency-oriented approaches for self-supervised speech representation learning Luis Lugo Valentin Vielzeuf SSL 19 1 0 18 Dec 2023
LeBenchmark 2.0: a Standardized, Replicable and Enhanced Framework for Self-supervised Representations of French Speech Titouan Parcollet H. Nguyen Solène Evain Marcely Zanon Boito Adrien Pupier ... François Portet Solange Rossato F. Ringeval D. Schwab Laurent Besacier 32 14 0 11 Sep 2023
Once-for-All Sequence Compression for Self-Supervised Speech Models Hsuan-Jui Chen Yen Meng Hung-yi Lee 6 4 0 04 Nov 2022
Multi-task self-supervised learning for Robust Speech Recognition Mirco Ravanelli Jianyuan Zhong Santiago Pascual P. Swietojanski João Monteiro J. Trmal Yoshua Bengio SSL 171 288 0 25 Jan 2020