LeBenchmark 2.0: a Standardized, Replicable and Enhanced Framework for Self-supervised Representations of French Speech

arXiv:2309.05472v2 Announce Type: replace
Abstract: Self-supervised learning (SSL) is at the origin of unprecedented improvements in many different domains including computer vision and natural language processing. Speech processing drastically benefitted from SSL as most of the current domain-related tasks are now being approached with pre-trained models. This work introduces LeBenchmark 2.0 an open-source framework for assessing and building SSL-equipped French speech technologies. It includes documented, large-scale and heterogeneous corpora with up to 14,000 hours of heterogeneous speech, ten pre-trained SSL …

abstract and natural language processing arxiv computer computer vision cs.ai cs.cl cs.sd current domain domains eess.as framework french improvements language language processing natural natural language natural language processing pre-trained models processing self-supervised learning speech speech processing ssl supervised learning tasks type vision