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Wyszukujesz frazę "emotion recognition" wg kryterium: Temat


Wyświetlanie 1-3 z 3
Tytuł:
Communication atmosphere in humans and robots interaction based on the concept of fuzzy atmosfield generated by emotional states of humans and robots
Autorzy:
Liu, Z. T.
Chen, L. F.
Dong, F. Y.
Hirota, K.
Min, W.
Li, D. Y.
Yamazaki, Y.
Powiązania:
https://bibliotekanauki.pl/articles/384920.pdf
Data publikacji:
2013
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
human-robot interaction
communication atmosphere
fuzzy logic
emotion recognition
Opis:
Communication atmosphere based on emotional states of humans and robots is modeled by using Fuzzy Atmosfield (FA), where the human emotion is estimated from bimodal communication cues (i.e., speech and gesture) using weighted fusion and fuzzy logic, and the robot emotion is generated by emotional expression synthesis. It makes possible to quantitatively express overall affective expression of individuals, and helps to facilitate smooth communication in humans-robots interaction. Experiments in a household environment are performed by four humans and five eye robots, where emotion recognition of humans based on bimodal cues achieves 84% accuracy in average, improved by about 10% compared to that using only speech. Experimental results from the model of communication atmosphere based on the FA are evaluated by comparing with questionnaire surveys, from which the maximum error of 0.25 and the minimum correlation coefficient of 0.72 for three axes in the FA confirm the validity of the proposal. In ongoing work, an atmosphere representation system is being planned for casual communication between humans and robots, taking into account multiple emotional modalities such as speech, gesture, and music.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2013, 7, 2; 52-63
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Speech emotion recognition system for social robots
Autorzy:
Juszkiewicz, Ł.
Powiązania:
https://bibliotekanauki.pl/articles/384511.pdf
Data publikacji:
2013
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
speech emotion recognition
prosody
machine learning
Emo-DB
intonation
social robot
Opis:
The paper presents a speech emotion recognition system for social robots. Emotions are recognised using global acoustic features of the speech. The system implements the speech parameters calculation, features extraction, features selection and classification. All these phases are described. The system was verified using the two emotional speech databases: Polish and German. Perspectives for using such system in the social robots are presented.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2013, 7, 4; 59-65
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Facial emotion recognition using average face ratios and fuzzy hamming distance
Autorzy:
Ounachad, Khalid
Oualla, Mohamed
Sadiq, Abdelalim
Souhar, Abdelghani
Powiązania:
https://bibliotekanauki.pl/articles/2141894.pdf
Data publikacji:
2020
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
average face ratios
facial emotion recognition
fuzzy hamming distance
perfect face ratios
Opis:
Facial emotion recognition (FER) is an important topic in the fields of computer vision and artificial intelligence owing to its significant academic and commercial potential. Nowadays, emotional factors are important as classic functional aspects of customer purchasing behavior. Purchasing choices and decisions making are the result of a careful analysis of the product advantages and disadvantages and of affective and emotional aspects. This paper presents a novel method for human emotion classification and recognition. We generate seven referential faces suitable for each kind of facial emotion based on perfect face ratios and some classical averages. The basic idea is to extract perfect face ratios for emotional face and for each referential face as features and calculate the distance between them by using fuzzy hamming distance. To extract perfect face ratios, we use the point landmarks in the face then sixteen features will be extract. An experimental evaluation demonstrates the satisfactory performance of our approach on WSEFEP dataset. It can be applied with any existing facial emotion dataset. The proposed algorithm will be a competitor of the other proposed relative approaches. The recognition rate reaches more than 90%.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2020, 14, 4; 37-44
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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