Self-Supervised Speech Representation Learning: A Review

Although supervised deep learning has revolutionized speech and audio processing, it has necessitated the building of specialist models for individual tasks and application scenarios. It is likewise difficult to apply this to dialects and languages for which only limited labeled data is available. S...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE journal of selected topics in signal processing Jg. 16; H. 6; S. 1179 - 1210
Hauptverfasser:	Mohamed, Abdelrahman, Lee, Hung-yi, Borgholt, Lasse, Havtorn, Jakob D., Edin, Joakim, Igel, Christian, Kirchhoff, Katrin, Li, Shang-Wen, Livescu, Karen, Maaloe, Lars, Sainath, Tara N., Watanabe, Shinji
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.10.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Acknowledgment Automatic speech recognition Computer vision Data Data models Data transmission Deep learning Dialects Domains Hidden Markov models Labeling Languages Learning Machine learning Modal data Natural language processing Regional dialects Representation Representation learning Representations Self-supervised learning Speech Speech processing Speech recognition speech representations Training Voice recognition
ISSN:	1932-4553, 1941-0484
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!