Hybrid Feature Embedded Sparse Stacked Autoencoder and Manifold Dimensionality Reduction Ensemble for Mental Health Speech Recognition

Speech feature learning is the key to speech mental health recognition. Deep feature learning can automatically extract the speech features but suffers from the small sample problem. The traditional feature extract method is effective, but cannot find the inter-feature structure to generate the new...

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Vydáno v:	IEEE access Ročník 9; s. 28729 - 28741
Hlavní autoři:	Chen, Hong, Lin, Yuan, Li, Yongming, Wang, Wei, Wang, Pin, Lei, Yan
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Piscataway IEEE 2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Algorithms Classification Classification algorithms Depression Embedded hybrid feature sparse stacked autoencoder ensemble learning Feature extraction feature fusion Feature recognition L1 regularization Machine learning Manifolds Mental health Speech speech mental health recognition Speech recognition Support vector machines Task analysis
ISSN:	2169-3536, 2169-3536
On-line přístup:	Získat plný text
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