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Volume 25, Issue 1 (Spring 2023)
Advances in Cognitive Sciences 2023, 25(1): 108-122 |
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Jandaghian M, Setayeshi S, Razzazi F, Sharifi A. Development of a cognitive machine for the evaluation of emotions in the Iranian musical Dastgahs using brain emotional learning. Advances in Cognitive Sciences 2023; 25 (1) :108-122
URL: http://icssjournal.ir/article-1-1485-en.html
URL: http://icssjournal.ir/article-1-1485-en.html
1- PhD Student of Artificial Intelligence, Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
2- Associate Professor, Department of Energy Engineering and Physics, Amirkabir University of Technology, Tehran, Iran
3- Associate Professor, Department of Electrical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
4- Assistant Professor, Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
2- Associate Professor, Department of Energy Engineering and Physics, Amirkabir University of Technology, Tehran, Iran
3- Associate Professor, Department of Electrical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
4- Assistant Professor, Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
Abstract: (934 Views)
Introduction
Iranian traditional music includes Dastgahs and Avazes, which can evoke different emotions. Many sources have divided Iranian musical Dastgahs into seven types (Shur, Mahur, Segah, Chahargah, Raste-Panjgah, Homayun, Nava) (12, 13). In recent years, several studies have been used for mood recognition or classification of music pieces based on Dastgah (14-16). Nevertheless, considering this collection wide range of emotions, diversity, and richness, it is necessary to examine the quantitative value of the different emotions evoked by the Dastgah of Iranian music. Famous musicians have qualitatively described the emotional features evoked by each Dastgah. For example, the sadness of the Segah (17) and the motivation and pleasure of Mahur (18, 19) have been emphasized. But there are two problems. Initially, a qualitative description is provided, with a limited number of studies focusing on the quantification of emotions evoked by Iranian musical Dastgahs. Secondly, not only musical experts but also ordinary people do not agree with the evoked emotions by each Dastgah. People's emotional backgrounds vary, influencing their comments on a particular Dastgah. Their musical knowledge also plays a role in shaping their opinions. Therefore, musical Dastgah can evoke different emotions in different individuals. The main goal of the current study is to predict the quantitative values of all the emotional features of Iranian musical Dastgahs, considering the emotional background of a specific person and the musical features of an Iranian music piece.
Methods
The design of the proposed system was based on the parallel processing of emotions in the brain (28). The Brain Emotional Learning (BEL) model expresses emotional learning based on the interaction of four neural regions of the brain, including the orbitofrontal, amygdala, thalamus, and cortex (25). Thayer's emotional model describes 12 emotions using two dimensions called arousal and valence (29). Based on Thayer's model, the emotional studied components are in order: pleased, happy, excited, annoyed, angry, nervous, sad, bored, sleepy, calm, peaceful, and relaxed.
According to the proposed structure, pieces of music enter the thalamus, and the thalamus removes the noise, converts the MIDI file to a matrix, and extracts the features based on the structure of Iranian traditional music. The output of the thalamus was sent to all the emotional parts for processing. Based on Thayer's model, the proposed structure included 12 emotional parts, each responsible for evaluating one of the emotions from the input matrix. The most impressive feature was the type of musical Dastgah (including one of the seven Dastgahs) directly imported from the thalamus to the amygdala. Dimensions of the Thayer model helped us to adjust the reinforcement signals. Arousal was used as a signal to the amygdala, and valence as a reinforcement signal to the orbitofrontal.
This study used “RADIF of Mirza Abdollah,” published with the composition and playing of Setar (an Iranian musical instrument) by Dariush Talaei (31). The researchers asked 52 participants to evaluate each piece’s 12 emotions of Thayer's emotional model. The simulation environment was MATLAB. The cross-validation method was used to evaluate each person's feelings. In this way, the samples were divided into seven equal parts with the normal distribution of parts based on the type of Dastgah, so five parts were used as training samples, and two parts were used as test samples. Twenty-one replications were performed to cover all possible scenarios.
Results
The proposed system was evaluated in two stages. In the first stage, the system’s overall performance compared to Anfis was reported so that the system’s output was confirmed with an acceptable error. Furthermore, this study used the coefficient of determination or R-Squared as another standard to evaluate the performance of the proposed system. In the second stage, the average emotions of all fifty-two participants were summarized and normalized based on the musical Dastgahs shown in Figure 1. Considering no similar study to compare the system's performance, referring to the qualitative description of the Khaleghi can confirm the results (17).
Fig. 1. Average emotions of all participants based on Dastgah
Overall, listeners were more successful in identifying arousal levels in the Dastgahs, but they struggled to discern the valence pattern because arousal is more comprehensible to humans than capacity. The ultimate outcome demonstrated that Dastgahs with higher arousal power, such as Shur and Mahur, had a lower average system error. Conversely, Dastgahs with lower valence power, like Nava and RastePangah, experienced a higher error rate.
Conclusion
This study was conducted to evaluate individual emotions of Iranian musical Dastgahs. This research tried to propose a model with special attention to the features of Iranian traditional music and the emotional background of the individual. The proposed model included 12 parts, each responsible for processing one emotion of Thayer's emotional model. All 12 parts worked in parallel with each other. Each part included four areas: orbitofrontal, amygdala, thalamus, and cortex. The most impressive feature was the type of Dastgah that entered the amygdala directly from the thalamus. Thayer's model has two dimensions: valence and arousal. The proposed model used valence to regulate the amygdala reinforcement signal and arousal to regulate the orbitofrontal reinforcement signal. The analysis of the results leads us to the existence of uncertainty caused by people's emotional background lies in the behavioral and physiological function of emotions in the brain.
Ethical Considerations
Compliance with ethical guidelines
The present study was conducted following ethical principles, including the consent of all participants, respect for the confidentiality of participants' information, and freedom to leave the research process.
Authors' contributions
All four authors prepared the study; the first author designed the model and the computational framework. The second author analyzed the data. The third and fourth authors did sample preparation. All of the authors contributed to the interpretation of the results.
Funding
No financial support has been received from any organization for this research.
Acknowledgments
The authors would like to thank all 52 participants in this study, as well as the respected professors who guided this work.
Conflicts of interest
All authors certify that they have no affiliations with or involvement in any organization or entity with any interest or non-financial interest in the subject matter or materials discussed in this manuscript.
Iranian traditional music includes Dastgahs and Avazes, which can evoke different emotions. Many sources have divided Iranian musical Dastgahs into seven types (Shur, Mahur, Segah, Chahargah, Raste-Panjgah, Homayun, Nava) (12, 13). In recent years, several studies have been used for mood recognition or classification of music pieces based on Dastgah (14-16). Nevertheless, considering this collection wide range of emotions, diversity, and richness, it is necessary to examine the quantitative value of the different emotions evoked by the Dastgah of Iranian music. Famous musicians have qualitatively described the emotional features evoked by each Dastgah. For example, the sadness of the Segah (17) and the motivation and pleasure of Mahur (18, 19) have been emphasized. But there are two problems. Initially, a qualitative description is provided, with a limited number of studies focusing on the quantification of emotions evoked by Iranian musical Dastgahs. Secondly, not only musical experts but also ordinary people do not agree with the evoked emotions by each Dastgah. People's emotional backgrounds vary, influencing their comments on a particular Dastgah. Their musical knowledge also plays a role in shaping their opinions. Therefore, musical Dastgah can evoke different emotions in different individuals. The main goal of the current study is to predict the quantitative values of all the emotional features of Iranian musical Dastgahs, considering the emotional background of a specific person and the musical features of an Iranian music piece.
Methods
The design of the proposed system was based on the parallel processing of emotions in the brain (28). The Brain Emotional Learning (BEL) model expresses emotional learning based on the interaction of four neural regions of the brain, including the orbitofrontal, amygdala, thalamus, and cortex (25). Thayer's emotional model describes 12 emotions using two dimensions called arousal and valence (29). Based on Thayer's model, the emotional studied components are in order: pleased, happy, excited, annoyed, angry, nervous, sad, bored, sleepy, calm, peaceful, and relaxed.
According to the proposed structure, pieces of music enter the thalamus, and the thalamus removes the noise, converts the MIDI file to a matrix, and extracts the features based on the structure of Iranian traditional music. The output of the thalamus was sent to all the emotional parts for processing. Based on Thayer's model, the proposed structure included 12 emotional parts, each responsible for evaluating one of the emotions from the input matrix. The most impressive feature was the type of musical Dastgah (including one of the seven Dastgahs) directly imported from the thalamus to the amygdala. Dimensions of the Thayer model helped us to adjust the reinforcement signals. Arousal was used as a signal to the amygdala, and valence as a reinforcement signal to the orbitofrontal.
This study used “RADIF of Mirza Abdollah,” published with the composition and playing of Setar (an Iranian musical instrument) by Dariush Talaei (31). The researchers asked 52 participants to evaluate each piece’s 12 emotions of Thayer's emotional model. The simulation environment was MATLAB. The cross-validation method was used to evaluate each person's feelings. In this way, the samples were divided into seven equal parts with the normal distribution of parts based on the type of Dastgah, so five parts were used as training samples, and two parts were used as test samples. Twenty-one replications were performed to cover all possible scenarios.
Results
The proposed system was evaluated in two stages. In the first stage, the system’s overall performance compared to Anfis was reported so that the system’s output was confirmed with an acceptable error. Furthermore, this study used the coefficient of determination or R-Squared as another standard to evaluate the performance of the proposed system. In the second stage, the average emotions of all fifty-two participants were summarized and normalized based on the musical Dastgahs shown in Figure 1. Considering no similar study to compare the system's performance, referring to the qualitative description of the Khaleghi can confirm the results (17).
Fig. 1. Average emotions of all participants based on Dastgah
Overall, listeners were more successful in identifying arousal levels in the Dastgahs, but they struggled to discern the valence pattern because arousal is more comprehensible to humans than capacity. The ultimate outcome demonstrated that Dastgahs with higher arousal power, such as Shur and Mahur, had a lower average system error. Conversely, Dastgahs with lower valence power, like Nava and RastePangah, experienced a higher error rate.
Conclusion
This study was conducted to evaluate individual emotions of Iranian musical Dastgahs. This research tried to propose a model with special attention to the features of Iranian traditional music and the emotional background of the individual. The proposed model included 12 parts, each responsible for processing one emotion of Thayer's emotional model. All 12 parts worked in parallel with each other. Each part included four areas: orbitofrontal, amygdala, thalamus, and cortex. The most impressive feature was the type of Dastgah that entered the amygdala directly from the thalamus. Thayer's model has two dimensions: valence and arousal. The proposed model used valence to regulate the amygdala reinforcement signal and arousal to regulate the orbitofrontal reinforcement signal. The analysis of the results leads us to the existence of uncertainty caused by people's emotional background lies in the behavioral and physiological function of emotions in the brain.
Ethical Considerations
Compliance with ethical guidelines
The present study was conducted following ethical principles, including the consent of all participants, respect for the confidentiality of participants' information, and freedom to leave the research process.
Authors' contributions
All four authors prepared the study; the first author designed the model and the computational framework. The second author analyzed the data. The third and fourth authors did sample preparation. All of the authors contributed to the interpretation of the results.
Funding
No financial support has been received from any organization for this research.
Acknowledgments
The authors would like to thank all 52 participants in this study, as well as the respected professors who guided this work.
Conflicts of interest
All authors certify that they have no affiliations with or involvement in any organization or entity with any interest or non-financial interest in the subject matter or materials discussed in this manuscript.
Keywords: Cognitive modeling, Evaluation of emotions, Iranian musical Dastgah, Brain emotional learning, RADIF of Mirza Abdollah
Type of Study: Research |
Received: 2022/11/8 | Accepted: 2023/05/8 | Published: 2023/07/10
Received: 2022/11/8 | Accepted: 2023/05/8 | Published: 2023/07/10
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