Cargando…
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...
Autores principales: | Nam, Youngja, Lee, Chankyu |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8271804/ https://www.ncbi.nlm.nih.gov/pubmed/34199027 http://dx.doi.org/10.3390/s21134399 |
Ejemplares similares
-
Noisy Ocular Recognition Based on Three Convolutional Neural Networks
por: Lee, Min Beom, et al.
Publicado: (2017) -
Speech Emotion Recognition Using Convolution Neural Networks and Multi-Head Convolutional Transformer
por: Ullah, Rizwan, et al.
Publicado: (2023) -
Speaker Recognition Using Constrained Convolutional Neural Networks in Emotional Speech
por: Simić, Nikola, et al.
Publicado: (2022) -
A method for enhancing speech and warning signals based on parallel convolutional neural networks in a noisy environment
por: Kang, Ha Lim, et al.
Publicado: (2021) -
Pre-trained Deep Convolution Neural Network Model With Attention for Speech Emotion Recognition
por: Zhang, Hua, et al.
Publicado: (2021)