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

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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Bibliographic Details
Main Authors: Hong Chen, Yuan Lin, Yongming Li, Wei Wang, Pin Wang, Yan Lei
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Embedded hybrid feature sparse stacked autoencoder
ensemble learning
feature fusion
L1 regularization
speech mental health recognition
Online Access:https://ieeexplore.ieee.org/document/9348883/

Internet

https://ieeexplore.ieee.org/document/9348883/

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