Cascaded Convolutional Neural Network Architecture for Speech Emotion Recognition in Noisy Conditions
Convolutional neural networks (CNNs) are a state-of-the-art technique for speech emotion recognition. However, CNNs have mostly been applied to noise-free emotional speech data, and limited evidence is available for their applicability in emotional speech denoising. In this study, a cascaded denoisi...
Main Authors: | Youngja Nam, Chankyu Lee |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-06-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/21/13/4399 |
Similar Items
-
Towards Reduced CNNs for De-Noising Phase Images Corrupted with Speckle Noise
by: Marie Tahon, et al.
Published: (2021-07-01) -
An Interferometric Phase Noise Reduction Method Based on Modified Denoising Convolutional Neural Network
by: Shuo Li, et al.
Published: (2020-01-01) -
Speaker Awareness for Speech Emotion Recognition
by: Gustavo Assunção, et al.
Published: (2020-04-01) -
Channel Estimation Capacity Enhancement for Multigroup Multicasting Multimedia Networks With DnCNN
by: Tianyi Zeng, et al.
Published: (2019-01-01) -
Facial Emotion Recognition Using Transfer Learning in the Deep CNN
by: M. A. H. Akhand, et al.
Published: (2021-04-01)