activity
20212024
most citedConditional independence for pretext task selection in Self-supervised speech representation learning

5 citations · 11 across the 10 of their papers we have counts for

collaborators

11 papers

cs.LG2024★ 3 cited

Open-Source Conversational AI with SpeechBrain 1.0

Mirco Ravanelli, Titouan Parcollet, Adel Moumen +30

SpeechBrain is an open-source Conversational AI toolkit based on PyTorch, focused particularly on speech processing tasks such as speech recognition, speech enhancement, speaker re…

eess.AS2024★ 1 cited

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…

cs.SD2024

How Should We Extract Discrete Audio Tokens from Self-Supervised Models?

Pooneh Mousavi, Jarod Duret, Salah Zaiem +4

Discrete audio tokens have recently gained attention for their potential to bridge the gap between audio and language processing. Ideal audio tokens must preserve content, paraling…

cs.CL2023

CL-MASR: A Continual Learning Benchmark for Multilingual ASR

Luca Della Libera, Pooneh Mousavi, Salah Zaiem +2

Modern multilingual automatic speech recognition (ASR) systems like Whisper have made it possible to transcribe audio in multiple languages with a single model. However, current st…

eess.AS2023

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…

eess.AS2023

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…

eess.AS2023

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…

eess.AS2023★ 2 cited

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…

eess.AS2022

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…

eess.AS2021

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…

eess.AS2021★ 5 cited

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…