textless-lib: a Library for Textless Spoken Language Processing
원문 초록
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/ .
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Spoken Language Modeling with Duration-Penalized Self-Supervised Units
AnCoGen: Analysis, Control and Generation of Speech with a Masked Autoencoder
EmphAssess : a Prosodic Benchmark on Assessing Emphasis Transfer in Speech-to-Speech Models
Weakly-supervised Contrastive Learning for Unsupervised Object Discovery
Speaker-Independent Acoustic-to-Articulatory Speech Inversion
Analysing Discrete Self Supervised Speech Representation for Spoken Language Modeling
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