Combining Spectral and Self-Supervised Features for Low Resource Speech Recognition and Translation

Self-Supervised Learning (SSL) models have been successfully applied in various deep learning-based speech tasks, particularly those with a limited amount of data. However, the quality of SSL representations depends highly on the relatedness between the SSL training domain(s) and the target data dom...

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Veröffentlicht in:	arXiv.org 2022-04
Hauptverfasser:	Berrebbi, Dan, Shi, Jiatong, Yan, Brian, Lopez-Francisco, Osbel, Amith, Jonathan D, Watanabe, Shinji
Format:	Artikel
Sprache:	eng
Schlagworte:	Automatic speech recognition Deep learning Domains Extractors Feature extraction Machine learning Representations Training Voice recognition
Online-Zugang:	Volltext
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