93 citations · 190 across the 13 of their papers we have counts for
4 papers · 1 filter
Speech Resynthesis from Discrete Disentangled Self-Supervised Representations
Adam Polyak, Yossi Adi, Jade Copet +5
We propose using self-supervised discrete representations for the task of speech resynthesis. To generate disentangled representation, we separately extract low-bitrate representat…
Learning spectro-temporal representations of complex sounds with parameterized neural networks
Rachid Riad, Julien Karadayi, Anne-Catherine Bachoud-Lévi +1
Deep Learning models have become potential candidates for auditory neuroscience research, thanks to their recent successes on a variety of auditory tasks. Yet, these models often l…
Generative Spoken Language Modeling from Raw Audio
Kushal Lakhotia, Evgeny Kharitonov, Wei-Ning Hsu +8
We introduce Generative Spoken Language Modeling, the task of learning the acoustic and linguistic characteristics of a language from raw audio (no text, no labels), and a set of m…
VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretation
Changhan Wang, Morgane Rivière, Ann Lee +6
We introduce VoxPopuli, a large-scale multilingual corpus providing 100K hours of unlabelled speech data in 23 languages. It is the largest open data to date for unsupervised repre…