most citedScaling Speech Technology to 1,000+ Languages

116 citations · 124 across the 6 of their papers we have counts for

collaborators

6 papers

eess.AS2023★ 1 cited

Low-Resource Self-Supervised Learning with SSL-Enhanced TTS

Po-chun Hsu, Ali Elkahky, Wei-Ning Hsu +6

Self-supervised learning (SSL) techniques have achieved remarkable results in various speech processing tasks. Nonetheless, a significant challenge remains in reducing the reliance…

cs.CL2023★ 116 cited

Scaling Speech Technology to 1,000+ Languages

Vineel Pratap, Andros Tjandra, Bowen Shi +13

Expanding the language coverage of speech technology has the potential to improve access to information for many more people. However, current speech technology is restricted to ab…

cs.CL2022

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…

cs.CL2022★ 3 cited

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…

cs.CL2022★ 4 cited

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…

cs.CL2022

Retrieve-and-Fill for Scenario-based Task-Oriented Semantic Parsing

Akshat Shrivastava, Shrey Desai, Anchit Gupta +4

Task-oriented semantic parsing models have achieved strong results in recent years, but unfortunately do not strike an appealing balance between model size, runtime latency, and cr…