Emotion Recognition System from Speech and Visual Information based on Convolutional Neural Networks
| Autor: | Liviu Cristian Dutu, Nicolae-Catalin Ristea, Anamaria Radoi |
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| Rok vydání: | 2019 |
| Předmět: |
FOS: Computer and information sciences
Scheme (programming language) Computer Science - Machine Learning Sound (cs.SD) Facial expression Point (typography) Computer science Computer Vision and Pattern Recognition (cs.CV) Speech recognition Computer Science - Computer Vision and Pattern Recognition Convolutional neural network Computer Science - Sound Field (computer science) Machine Learning (cs.LG) Domain (software engineering) Action (philosophy) Audio and Speech Processing (eess.AS) FOS: Electrical engineering electronic engineering information engineering Spectrogram computer Electrical Engineering and Systems Science - Audio and Speech Processing computer.programming_language |
| Zdroj: | SpeD |
| DOI: | 10.1109/sped.2019.8906538 |
| Popis: | Emotion recognition has become an important field of research in the human-computer interactions domain. The latest advancements in the field show that combining visual with audio information lead to better results if compared to the case of using a single source of information separately. From a visual point of view, a human emotion can be recognized by analyzing the facial expression of the person. More precisely, the human emotion can be described through a combination of several Facial Action Units. In this paper, we propose a system that is able to recognize emotions with a high accuracy rate and in real time, based on deep Convolutional Neural Networks. In order to increase the accuracy of the recognition system, we analyze also the speech data and fuse the information coming from both sources, i.e., visual and audio. Experimental results show the effectiveness of the proposed scheme for emotion recognition and the importance of combining visual with audio data. |
| Databáze: | OpenAIRE |
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