278 citations · 792 across the 28 of their papers we have counts for
7 papers · 1 filter
AudioPaLM: A Large Language Model That Can Speak and Listen
Paul K. Rubenstein, Chulayuth Asawaroengchai, Duc Dung Nguyen +27
We introduce AudioPaLM, a large language model for speech understanding and generation. AudioPaLM fuses text-based and speech-based language models, PaLM-2 [Anil et al., 2023] and…
Fully Convolutional Speech Recognition
Neil Zeghidour, Qiantong Xu, Vitaliy Liptchinsky +3
Current state-of-the-art speech recognition systems build on recurrent neural networks for acoustic and/or language modeling, and rely on feature extraction pipelines to extract me…
Learning to detect dysarthria from raw speech
Juliette Millet, Neil Zeghidour
Speech classifiers of paralinguistic traits traditionally learn from diverse hand-crafted low-level features, by selecting the relevant information for the task at hand. We explore…
End-to-End Speech Recognition From the Raw Waveform
Neil Zeghidour, Nicolas Usunier, Gabriel Synnaeve +2
State-of-the-art speech recognition systems rely on fixed, hand-crafted features such as mel-filterbanks to preprocess the waveform before the training pipeline. In this paper, we…
Sampling strategies in Siamese Networks for unsupervised speech representation learning
Rachid Riad, Corentin Dancette, Julien Karadayi +3
Recent studies have investigated siamese network architectures for learning invariant speech representations using same-different side information at the word level. Here we invest…
Learning Filterbanks from Raw Speech for Phone Recognition
Neil Zeghidour, Nicolas Usunier, Iasonas Kokkinos +3
We train a bank of complex filters that operates on the raw waveform and is fed into a convolutional neural network for end-to-end phone recognition. These time-domain filterbanks…
Learning weakly supervised multimodal phoneme embeddings
Rahma Chaabouni, Ewan Dunbar, Neil Zeghidour +1
Recent works have explored deep architectures for learning multimodal speech representation (e.g. audio and images, articulation and audio) in a supervised way. Here we investigate…