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- W4205587935 abstract "Massive advancements in technology has made it possible to enable human and computer interaction which was once unimaginable. As the new modalities of the Human computer interaction through voice, gesture, brain signals have reached the market, rapid migration to those have been noticed from the regular keyboard and mouse interaction. Despite of various technical advancements, complete understanding of emotions as that of natural interactions remain missing leaving a huge space for research in that area. Beyond the verbal communication, emotions are key aspect of expressing oneself in human-human interaction and the need of understanding that emotions play a vital role in many computer applications. This paper explores all the existing ways of human-computer interactions that are currently in practice to enable the computer to understand the user’s emotions. In this paper, emotional data in various format from different sources were taken and their results were fused, and analyses has been carried out. The sources used for emotional data were the emotions in recorded speech, emotion in textual data and emotions through EEG signals. In recorded speech, acoustic features of the audio data were analysed by extracting the features with the help of LIBROSA library in Python. Fusion of the analysis result from the three sources helps in improving the accuracy of the emotion detection. Applications with emotion detection technology have wide range of applications in that would benefit companies in gain better understanding of their customers." @default.
- W4205587935 created "2022-01-26" @default.
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- W4205587935 creator A5076931431 @default.
- W4205587935 date "2021-10-08" @default.
- W4205587935 modified "2023-10-16" @default.
- W4205587935 title "Simultaneous Detection And Analysis Of Multi-Source Data In Prediction Of Human Emotion" @default.
- W4205587935 doi "https://doi.org/10.1109/icaeca52838.2021.9675654" @default.
- W4205587935 hasPublicationYear "2021" @default.
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