4 code implementations • NeurIPS 2023 • Rithesh Kumar, Prem Seetharaman, Alejandro Luebs, Ishaan Kumar, Kundan Kumar
Language models have been successfully used to model natural signals, such as images, speech, and music.
6 code implementations • 7 Jul 2021 • Neil Zeghidour, Alejandro Luebs, Ahmed Omran, Jan Skoglund, Marco Tagliasacchi
We present SoundStream, a novel neural audio codec that can efficiently compress speech, music and general audio at bitrates normally targeted by speech-tailored codecs.
1 code implementation • 23 Feb 2021 • Tom Denton, Alejandro Luebs, Felicia S. C. Lim, Andrew Storus, Hengchin Yeh, W. Bastiaan Kleijn, Jan Skoglund
Recent advances in neural-network based generative modeling of speech has shown great potential for speech coding.
1 code implementation • 18 Feb 2021 • W. Bastiaan Kleijn, Andrew Storus, Michael Chinen, Tom Denton, Felicia S. C. Lim, Alejandro Luebs, Jan Skoglund, Hengchin Yeh
We introduce predictive-variance regularization to reduce the sensitivity to outliers, resulting in a significant increase in performance.
no code implementations • 14 Oct 2019 • Cristina Gârbacea, Aäron van den Oord, Yazhe Li, Felicia S. C. Lim, Alejandro Luebs, Oriol Vinyals, Thomas C. Walters
In order to efficiently transmit and store speech signals, speech codecs create a minimally redundant representation of the input signal which is then decoded at the receiver with the best possible perceptual quality.
1 code implementation • 1 Dec 2017 • W. Bastiaan Kleijn, Felicia S. C. Lim, Alejandro Luebs, Jan Skoglund, Florian Stimberg, Quan Wang, Thomas C. Walters
Traditional parametric coding of speech facilitates low rate but provides poor reconstruction quality because of the inadequacy of the model used.