Self-Supervised End-to-End ASR for Low Resource L2 Swedish
Ragheb Al-Ghezi, Yaroslav Getman, Aku Rouhe, Raili Hildén, Mikko Kurimo
Abstract
Funding Information: This work is part of Digitala project which is funded by the Academy of Finland (grant numbers 322619, 322625, 322965). The computational resources were provided by Aalto ScienceIT. Funding Information: This work is part of Digitala project which is funded by the Academy of Finland (grant numbers 322619, 322625, 322965). The computational resources were provided by Aalto Scien-ceIT. Publisher Copyright: Copyright © 2021 ISCA.
Topics & Concepts
Computer scienceEnd-to-end principleSpeech recognitionArtificial intelligenceSpeech Recognition and SynthesisNatural Language Processing TechniquesTopic Modeling