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An autoencoder-based feature level fusion for speech emotion recognition

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成果类型:
期刊论文
作者:
Peng Shixin;Chen Kai;Tian Tian;Chen Jingying*
通讯作者:
Chen Jingying
作者机构:
[Peng Shixin; Chen Kai; Tian Tian; Chen Jingying] National Engineering Research Center for E-Learning, National Engineering Laboratory for Educational Big Data, Central China Normal University, Hubei, 430079, China
通讯机构:
[Chen Jingying] N
National Engineering Research Center for E-Learning, National Engineering Laboratory for Educational Big Data, Central China Normal University, Hubei, 430079, China
语种:
英文
关键词:
Attention mechanism;Autoencoder;Bimodal fusion;Emotion recognition
期刊:
数字通信与网络:英文版
ISSN:
2352-8648
年:
2022
机构署名:
本校为第一且通讯机构
院系归属:
国家数字化学习工程技术研究中心
摘要:
Although speech emotion recognition is challenging, it has broad application prospects in human-computer interaction. Building a system that can accurately and stably recognize emotions from human languages can provide a better user experience. However, the current unimodal emotion feature representations are not distinctive enough to accomplish the recognition, and they do not effectively simulate the inter-modality dynamics in speech emotion recognition tasks. This paper proposes a multimodal method that utilizes both audio and semantic content for speech emotion recognition. The proposed me...

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