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 paper, we introduce textless-lib, a PyTorch-based library aimed to facilitate research in this research area. We describe the building blocks that the library provides and demonstrate its usability by discuss three different use-case examples: (i) speaker probing, (ii) speech resynthesis and compression, and (iii) speech continuation. We believe that textless-lib substantially simplifies research the textless setting and will be handful not only for speech researchers but also for the NLP community at large. The code, documentation, and pre-trained models are available at https://github.com/facebookresearch/textlesslib/ .
@article{arxiv.2202.07359,
title = {textless-lib: a Library for Textless Spoken Language Processing},
author = {Eugene Kharitonov and Jade Copet and Kushal Lakhotia and Tu Anh Nguyen and Paden Tomasello and Ann Lee and Ali Elkahky and Wei-Ning Hsu and Abdelrahman Mohamed and Emmanuel Dupoux and Yossi Adi},
journal= {arXiv preprint arXiv:2202.07359},
year = {2022}
}
Comments
The library is available here https://github.com/facebookresearch/textlesslib/