Semi-Supervised Learning with Sparse Autoencoders in Automatic Speech Recognition
This work is aimed at exploring semi-supervised learning techniques to improve the performance of Automatic Speech Recognition systems. Semi-supervised learning takes advantage of unlabeled data in order to improve the quality of the representations extracted from the data.The proposed model is a ne...
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| Format: | Others |
| Language: | English |
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KTH, Skolan för datavetenskap och kommunikation (CSC)
2016
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-197628 |