Theoretical learning guarantees applied to acoustic modeling
Abstract In low-resource scenarios, for example, small datasets or a lack in computational resources available, state-of-the-art deep learning methods for speech recognition have been known to fail. It is possible to achieve more robust models if care is taken to ensure the learning guarantees provi...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
Sociedade Brasileira de Computação
2019-01-01
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Series: | Journal of the Brazilian Computer Society |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1186/s13173-018-0081-3 |