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Longxin Yao, Yun Lu, Mingjiang Wang, Yukun Qian and Heng Li
The construction of complex networks from electroencephalography (EEG) proves to be an effective method for representing emotion patterns in affection computing as it offers rich spatiotemporal EEG features associated with brain emotions. In this paper, ...
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Peranut Nimitsurachat and Peter Washington
Emotion recognition models using audio input data can enable the development of interactive systems with applications in mental healthcare, marketing, gaming, and social media analysis. While the field of affective computing using audio data is rich, a m...
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Zhichao Peng, Wenhua He, Yongwei Li, Yegang Du and Jianwu Dang
Speech emotion recognition is a critical component for achieving natural human?robot interaction. The modulation-filtered cochleagram is a feature based on auditory modulation perception, which contains multi-dimensional spectral?temporal modulation repr...
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Ismail Shahin, Ali Bou Nassif, Rameena Thomas and Shibani Hamsa
Modern developments in machine learning methodology have produced effective approaches to speech emotion recognition. The field of data mining is widely employed in numerous situations where it is possible to predict future outcomes by using the input se...
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Jingxia Chen, Yang Liu, Wen Xue, Kailei Hu and Wentao Lin
EEG-based emotion recognition has become an important part of human?computer interaction. To solve the problem that single-modal features are not complete enough, in this paper, we propose a multimodal emotion recognition method based on the attention re...
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Konlakorn Wongpatikaseree, Sattaya Singkul, Narit Hnoohom and Sumeth Yuenyong
Language resources are the main factor in speech-emotion-recognition (SER)-based deep learning models. Thai is a low-resource language that has a smaller data size than high-resource languages such as German. This paper describes the framework of using a...
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Yang Liu, Rui Li, Shunli Wang, Huayi Wu and Zhipeng Gui
Social media is increasingly being used to obtain timely flood information to assist flood disaster management and situational awareness. However, since data in social media are massive, redundant, and unstructured, it is tricky to intuitively and clearl...
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Yue Ma, Changlong Ling and Jing Wu
The benefits of the natural environment in urban space have been explored in numerous studies. However, only a few statistics and studies have been conducted on the correlation between emotion and urban waterfront space, especially considering gender dif...
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Joël Colloc
The purpose of this extension of the ESM?2019 conference paper is to propose some means to implement an artificial thinking model that simulates human psychological behavior. The first necessary model is the time fuzzy vector space model (TFVS). Traditio...
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Fei Yan, Abdullah M. Iliyasu, Sihao Jiao and Huamin Yang
Utilising the properties of quantum mechanics, i.e., entanglement, parallelism, etc., a quantum structure is proposed for representing and manipulating emotion space of robots. This quantum emotion space (QES) provides a mechanism to extend emotion inter...
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