Two stage emotion recognition based on speaking rate

2010 ◽  
Vol 14 (1) ◽  
pp. 35-48 ◽  
Author(s):  
Shashidhar G. Koolagudi ◽  
Rao Sreenivasa Krothapalli
Keyword(s):  
Emotion Recognition ◽  
Speaking Rate ◽  
Two Stage

scholarly journals IMPROVED SPEAKER-INDEPENDENT EMOTION RECOGNITION FROM SPEECH USING TWO-STAGE FEATURE REDUCTION

2015 ◽  
Vol 14 ◽  
pp. 57-76
Author(s):  
Hasrul Mohd Nazid ◽  
Hariharan Muthusamy ◽  
Vikneswaran Vijean ◽  
Sazali Yaacob
Keyword(s):  
Emotion Recognition ◽  
Feature Reduction ◽  
Two Stage ◽  
Speaker Independent

scholarly journals Two-level attention with two-stage multi-task learning for facial emotion recognition

2019 ◽  
Vol 62 ◽  
pp. 217-225 ◽  
Author(s):  
Wang Xiaohua ◽  
Peng Muzi ◽  
Pan Lijuan ◽  
Hu Min ◽  
Jin Chunhua ◽  
...  
Keyword(s):  
Emotion Recognition ◽  
Facial Emotion Recognition ◽  
Facial Emotion ◽  
Two Stage ◽  
Task Learning

scholarly journals IMPROVED SPEAKER-INDEPENDENT EMOTION RECOGNITION FROM SPEECH USING TWO-STAGE FEATURE REDUCTION

2015 ◽  
Author(s):  
Hasrul Mohd Nazid ◽  
Hariharan Muthusamy ◽  
Vikneswaran Vijean ◽  
Sazali Yaacob
Keyword(s):  
Emotion Recognition ◽  
Principal Component ◽  
Feature Reduction ◽  
Speech Emotion Recognition ◽  
Emotional Speech ◽  
Two Stage ◽  
Linear Discriminant ◽  
Speaker Independent ◽  
Speech Features ◽  
And Gender

In the recent years, researchers are focusing to improve the accuracy of speech emotion recognition. Generally, high emotion recognition accuracies were obtained for two-class emotion recognition, but multi-class emotion recognition is still a challenging task . The main aim of this work is to propose a two-stage feature reduction using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) for improving the accuracy of the speech emotion recognition (ER) system. Short-term speech features were extracted from the emotional speech signals. Experiments were carried out using four different supervised classifi ers with two different emotional speech databases. From the experimental results, it can be inferred that the proposed method provides better accuracies of 87.48% for speaker dependent (SD) and gender dependent (GD) ER experiment, 85.15% for speaker independent (SI) ER experiment, and 87.09% for gender independent (GI) experiment.  

scholarly journals Two-Stage Recognition and beyond for Compound Facial Emotion Recognition

Electronics ◽  
2021 ◽  
Vol 10 (22) ◽  
pp. 2847
Author(s):  
Dorota Kamińska ◽  
Kadir Aktas ◽  
Davit Rizhinashvili ◽  
Danila Kuklyanov ◽  
Abdallah Hussein Sham ◽  
...  
Keyword(s):  
Emotion Recognition ◽  
Complex Problem ◽  
Facial Emotion Recognition ◽  
Facial Emotion ◽  
Facial Features ◽  
Recognition Method ◽  
Two Stage ◽  
Facial Images ◽  
Emotion Labels

Facial emotion recognition is an inherently complex problem due to individual diversity in facial features and racial and cultural differences. Moreover, facial expressions typically reflect the mixture of people’s emotional statuses, which can be expressed using compound emotions. Compound facial emotion recognition makes the problem even more difficult because the discrimination between dominant and complementary emotions is usually weak. We have created a database that includes 31,250 facial images with different emotions of 115 subjects whose gender distribution is almost uniform to address compound emotion recognition. In addition, we have organized a competition based on the proposed dataset, held at FG workshop 2020. This paper analyzes the winner’s approach—a two-stage recognition method (1st stage, coarse recognition; 2nd stage, fine recognition), which enhances the classification of symmetrical emotion labels.

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