425 citations · 886 across the 37 of their papers we have counts for
9 papers · 1 filter
Pushing the performances of ASR models on English and Spanish accents
Pooja Chitkara, Morgane Riviere, Jade Copet +2
Speech to text models tend to be trained and evaluated against a single target accent. This is especially true for English for which native speakers from the United States became t…
Audio Language Modeling using Perceptually-Guided Discrete Representations
Felix Kreuk, Yaniv Taigman, Adam Polyak +4
In this work, we study the task of Audio Language Modeling, in which we aim at learning probabilistic models for audio that can be used for generation and completion. We use a stat…
High Fidelity Neural Audio Compression
Alexandre Défossez, Jade Copet, Gabriel Synnaeve +1
We introduce a state-of-the-art real-time, high-fidelity, audio codec leveraging neural networks. It consists in a streaming encoder-decoder architecture with quantized latent spac…
Brouhaha: multi-task training for voice activity detection, speech-to-noise ratio, and C50 room acoustics estimation
Marvin Lavechin, Marianne Métais, Hadrien Titeux +7
Most automatic speech processing systems register degraded performance when applied to noisy or reverberant speech. But how can one tell whether speech is noisy or reverberant? We…
Augmentation Invariant Discrete Representation for Generative Spoken Language Modeling
Itai Gat, Felix Kreuk, Tu Anh Nguyen +5
Generative Spoken Language Modeling research focuses on optimizing speech Language Models (LMs) using raw audio recordings without accessing any textual supervision. Such speech LM…
AudioGen: Textually Guided Audio Generation
Felix Kreuk, Gabriel Synnaeve, Adam Polyak +6
We tackle the problem of generating audio samples conditioned on descriptive text captions. In this work, we propose AaudioGen, an auto-regressive generative model that generates a…
STOP: A dataset for Spoken Task Oriented Semantic Parsing
Paden Tomasello, Akshat Shrivastava, Daniel Lazar +12
End-to-end spoken language understanding (SLU) predicts intent directly from audio using a single model. It promises to improve the performance of assistant systems by leveraging a…
Generative Spoken Dialogue Language Modeling
Tu Anh Nguyen, Eugene Kharitonov, Jade Copet +8
We introduce dGSLM, the first "textless" model able to generate audio samples of naturalistic spoken dialogues. It uses recent work on unsupervised spoken unit discovery coupled wi…
textless-lib: a Library for Textless Spoken Language Processing
Eugene Kharitonov, Jade Copet, Kushal Lakhotia +8
Textless spoken language processing research aims to extend the applicability of standard NLP toolset onto spoken language and languages with few or no textual resources. In this p…