The Intelligent Recognition of Speech Emotions: Survey Study
Speech emotion recognition (SER) is a challenging task in the field of artificial intelligence and machine learning. Over the years, researchers have proposed various approaches to recognize emotions from speech signals. This article will analyze and discuss some of the previous works on machine lea...
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| Format: | Article |
| Language: | English |
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Mosul University
2023-12-01
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| Series: | Al-Rafidain Journal of Computer Sciences and Mathematics |
| Subjects: | |
| Online Access: | https://csmj.mosuljournals.com/article_181626_2ad8762bf8d306aade4288932865e8d8.pdf |
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| _version_ | 1849308659017842688 |
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| author | Ali Abdulwahhab Yehya al_saffar Fawziya Ramo |
| author_facet | Ali Abdulwahhab Yehya al_saffar Fawziya Ramo |
| author_sort | Ali Abdulwahhab Yehya al_saffar |
| collection | DOAJ |
| description | Speech emotion recognition (SER) is a challenging task in the field of artificial intelligence and machine learning. Over the years, researchers have proposed various approaches to recognize emotions from speech signals. This article will analyze and discuss some of the previous works on machine learning and deep learning in SER. This survey study focuses on the importance of the human voice in determining emotional and psychological states. Various methods were used to successfully classify emotions such as anger, sadness, happiness, fear, disgust, neutral, and surprise. Reviewed in this study was conducted in sequential stages including pre-processing treatment, feature selection, classification, and evaluation of results. different data sets were also reviewed for international languages such as English, Hindi, German, Urdu, Tamil, French, and Arabic. The study primarily focused on artificial intelligence and machine learning algorithms due to their flexibility and ease of understanding with distinct results. |
| format | Article |
| id | doaj-art-0ec1874c72294e67aa159ffbc24d638f |
| institution | Kabale University |
| issn | 1815-4816 2311-7990 |
| language | English |
| publishDate | 2023-12-01 |
| publisher | Mosul University |
| record_format | Article |
| series | Al-Rafidain Journal of Computer Sciences and Mathematics |
| spelling | doaj-art-0ec1874c72294e67aa159ffbc24d638f2025-08-20T03:54:24ZengMosul UniversityAl-Rafidain Journal of Computer Sciences and Mathematics1815-48162311-79902023-12-0117211010.33899/csmj.2023.181626181626The Intelligent Recognition of Speech Emotions: Survey StudyAli Abdulwahhab Yehya al_saffar0Fawziya RamoMinistry of Higher Education and Practical Research / University of MosulSpeech emotion recognition (SER) is a challenging task in the field of artificial intelligence and machine learning. Over the years, researchers have proposed various approaches to recognize emotions from speech signals. This article will analyze and discuss some of the previous works on machine learning and deep learning in SER. This survey study focuses on the importance of the human voice in determining emotional and psychological states. Various methods were used to successfully classify emotions such as anger, sadness, happiness, fear, disgust, neutral, and surprise. Reviewed in this study was conducted in sequential stages including pre-processing treatment, feature selection, classification, and evaluation of results. different data sets were also reviewed for international languages such as English, Hindi, German, Urdu, Tamil, French, and Arabic. The study primarily focused on artificial intelligence and machine learning algorithms due to their flexibility and ease of understanding with distinct results.https://csmj.mosuljournals.com/article_181626_2ad8762bf8d306aade4288932865e8d8.pdfmachine learningdeep learningsermfccfeature extractioncnn |
| spellingShingle | Ali Abdulwahhab Yehya al_saffar Fawziya Ramo The Intelligent Recognition of Speech Emotions: Survey Study Al-Rafidain Journal of Computer Sciences and Mathematics machine learning deep learning ser mfcc feature extraction cnn |
| title | The Intelligent Recognition of Speech Emotions: Survey Study |
| title_full | The Intelligent Recognition of Speech Emotions: Survey Study |
| title_fullStr | The Intelligent Recognition of Speech Emotions: Survey Study |
| title_full_unstemmed | The Intelligent Recognition of Speech Emotions: Survey Study |
| title_short | The Intelligent Recognition of Speech Emotions: Survey Study |
| title_sort | intelligent recognition of speech emotions survey study |
| topic | machine learning deep learning ser mfcc feature extraction cnn |
| url | https://csmj.mosuljournals.com/article_181626_2ad8762bf8d306aade4288932865e8d8.pdf |
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