Exploring Deep Spectrum Representations via Attention-Based Recurrent and Convolutional Neural Networks for Speech Emotion Recognition

Exploring Deep Spectrum Representations via Attention-Based Recurrent and Convolutional Neural Networks for Speech Emotion Recognition

The automatic detection of an emotional state from human speech, which plays a crucial role in the area of human-machine interaction, has consistently been shown to be a difficult task for machine learning algorithms. Previous work on emotion recognition has mostly focused on the extraction of caref...

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Bibliographic Details
Main Authors: Ziping Zhao, Zhongtian Bao, Yiqin Zhao, Zixing Zhang, Nicholas Cummins, Zhao Ren, Bjorn Schuller
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Speech emotion recognition
bidirectional long short-term memory
fully convolutional networks
attention mechanism
spectrogram representation
Online Access:https://ieeexplore.ieee.org/document/8762126/

Internet

https://ieeexplore.ieee.org/document/8762126/

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