End-to-end Jordanian dialect speech-to-text self-supervised learning framework

End-to-end Jordanian dialect speech-to-text self-supervised learning framework

Speech-to-text engines are extremely needed nowadays for different applications, representing an essential enabler in human–robot interaction. Still, some languages suffer from the lack of labeled speech data, especially in the Arabic dialects or any low-resource languages. The need for a self-super...

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Bibliographic Details
Main Authors: Ali A. Safieh, Ibrahim Abu Alhaol, Rawan Ghnemat
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-12-01
Series:Frontiers in Robotics and AI
Subjects:
transformers
Wav2Vec
self-supervised
speech-to-text
self-training
HCI
Online Access:https://www.frontiersin.org/articles/10.3389/frobt.2022.1090012/full

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https://www.frontiersin.org/articles/10.3389/frobt.2022.1090012/full

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