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ShEMO: a large-scale validated database for persian speech emotion detection
, Article Language Resources and Evaluation ; 2018 ; 1574020X (ISSN) ; Jamshid Lou, P ; Karami, M ; Sharif University of Technology
Springer Netherlands
2018
Abstract
This paper introduces a large-scale, validated database for Persian called Sharif Emotional Speech Database (ShEMO). The database includes 3000 semi-natural utterances, equivalent to 3 h and 25 min of speech data extracted from online radio plays. The ShEMO covers speech samples of 87 native-Persian speakers for five basic emotions including anger, fear, happiness, sadness and surprise, as well as neutral state. Twelve annotators label the underlying emotional state of utterances and majority voting is used to decide on the final labels. According to the kappa measure, the inter-annotator agreement is 64% which is interpreted as “substantial agreement”. We also present benchmark results...
ShEMO: a large-scale validated database for Persian speech emotion detection
, Article Language Resources and Evaluation ; Volume 53, Issue 1 , 2019 ; 1574020X (ISSN) ; Jamshid Lou, P ; Karami, M ; Sharif University of Technology
Springer Netherlands
2019
Abstract
This paper introduces a large-scale, validated database for Persian called Sharif Emotional Speech Database (ShEMO). The database includes 3000 semi-natural utterances, equivalent to 3 h and 25 min of speech data extracted from online radio plays. The ShEMO covers speech samples of 87 native-Persian speakers for five basic emotions including anger, fear, happiness, sadness and surprise, as well as neutral state. Twelve annotators label the underlying emotional state of utterances and majority voting is used to decide on the final labels. According to the kappa measure, the inter-annotator agreement is 64% which is interpreted as “substantial agreement”. We also present benchmark results...
Controlling Emotional State by Environmental Modification
, M.Sc. Thesis Sharif University of Technology ; Bagheri Shouraki, Saeed (Supervisor)
Abstract
With the development of artificial intelligence as well as robotics, affective computing which is about recognizing human emotions by machines and creating artificial emotions in them in order to create a proper social reaction is becoming an important topic. Most of the research in this field has been focused on recognizing and detecting human emotions. In this study, assuming a proper understanding of emotions by artificial intelligence models, an attempt has been made to better clarify the emotional space. In more detail, the goal is to examine the changes in the human emotional state in order to gain better control of his behavior. In this study, by analyzing the feelings of users and...
The Emotion Recognition of Social Media Users’ Comments during Covid-19 Outbreak
, M.Sc. Thesis Sharif University of Technology ; Rezaei, Saeed (Supervisor) ; Bahrani, Mohammad (Supervisor)
Abstract
In the last three years, the lives of many people around the world have changed with the spread of the Corona virus. In order to better manage the consequences related to the spread of this disease, extensive research has been done on this virus, and researchers in data science and artificial intelligence have devoted a part of their research to studying the effects of this virus on the people in one or different societies.On the other hand, the study of social networks about a specific issue or trend topic, allows us to examine more closely the atmosphere that governs the society and analyze the emotions, feelings and the level of concern of the members of the society about that issue.The...