5 citations · 11 across the 10 of their papers we have counts for
8 papers · 1 filter
Less Forgetting for Better Generalization: Exploring Continual-learning Fine-tuning Methods for Speech Self-supervised Representations
Salah Zaiem, Titouan Parcollet, Slim Essid
Despite being trained on massive and diverse datasets, speech self-supervised encoders are generally used for downstream purposes as mere frozen feature extractors or model initial…
Speech Self-Supervised Representations Benchmarking: a Case for Larger Probing Heads
Salah Zaiem, Youcef Kemiche, Titouan Parcollet +2
Self-supervised learning (SSL) leverages large datasets of unlabeled speech to reach impressive performance with reduced amounts of annotated data. The high number of proposed appr…
Automatic Data Augmentation for Domain Adapted Fine-Tuning of Self-Supervised Speech Representations
Salah Zaiem, Titouan Parcollet, Slim Essid
Self-Supervised Learning (SSL) has allowed leveraging large amounts of unlabeled speech data to improve the performance of speech recognition models even with small annotated datas…
Speech Self-Supervised Representation Benchmarking: Are We Doing it Right?
Salah Zaiem, Youcef Kemiche, Titouan Parcollet +2
Self-supervised learning (SSL) has recently allowed leveraging large datasets of unlabeled speech signals to reach impressive performance on speech tasks using only small amounts o…
Fine-tuning Strategies for Faster Inference using Speech Self-Supervised Models: A Comparative Study
Salah Zaiem, Robin Algayres, Titouan Parcollet +2
Self-supervised learning (SSL) has allowed substantial progress in Automatic Speech Recognition (ASR) performance in low-resource settings. In this context, it has been demonstrate…
Automatic Data Augmentation Selection and Parametrization in Contrastive Self-Supervised Speech Representation Learning
Salah Zaiem, Titouan Parcollet, Slim Essid
Contrastive learning enables learning useful audio and speech representations without ground-truth labels by maximizing the similarity between latent representations of similar sig…
Pretext Tasks selection for multitask self-supervised speech representation learning
Salah Zaiem, Titouan Parcollet, Slim Essid +1
Through solving pretext tasks, self-supervised learning leverages unlabeled data to extract useful latent representations replacing traditional input features in the downstream tas…
Conditional independence for pretext task selection in Self-supervised speech representation learning
Salah Zaiem, Titouan Parcollet, Slim Essid
Through solving pretext tasks, self-supervised learning (SSL) leverages unlabeled data to extract useful latent representations replacing traditional input features in the downstre…