Voice-Based Emotion Identification Based on Mel Frequency Cepstral Coefficient Feature Extraction Using Self-Organized Maps and Radial Basis Function
Speech recognition is one of the most popular research fields, one of which is about emotion identification. Voice-based emotion identification is carried out to determine the pattern of emotions using the depth analysis mechanism of voice signal development and feature extraction that carries the e...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Universitas Airlangga
2025-03-01
|
| Series: | Contemporary Mathematics and Applications (ConMathA) |
| Online Access: | https://e-journal.unair.ac.id/CONMATHA/article/view/68246 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849720410749272064 |
|---|---|
| author | Asrivatun Nikmah Auli Damayanti Edi Winarko |
| author_facet | Asrivatun Nikmah Auli Damayanti Edi Winarko |
| author_sort | Asrivatun Nikmah |
| collection | DOAJ |
| description | Speech recognition is one of the most popular research fields, one of which is about emotion identification. Voice-based emotion identification is carried out to determine the pattern of emotions using the depth analysis mechanism of voice signal development and feature extraction that carries the emotional characteristic parameters of the speaker's voice. Furthermore, the emotional characteristics of the speaker's voice are classified using an artificial neural network method to recognize patterns. In this study, emotion identification from voice signal data is classified into angry, sad, happy, and neutral emotions. The stages of voice-based emotion identification, including the feature extraction stage using the mel frequency cepstral coefficient, produce coefficient values, which will be used in the identification stage using the Self Organized Maps method on the Radial Basis Function. |
| format | Article |
| id | doaj-art-8ed9f8bcb1de4d5bb0a3ade3f454efc1 |
| institution | DOAJ |
| issn | 2686-5564 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Universitas Airlangga |
| record_format | Article |
| series | Contemporary Mathematics and Applications (ConMathA) |
| spelling | doaj-art-8ed9f8bcb1de4d5bb0a3ade3f454efc12025-08-20T03:11:55ZengUniversitas AirlanggaContemporary Mathematics and Applications (ConMathA)2686-55642025-03-0171364510.20473/conmatha.v7i1.6824666434Voice-Based Emotion Identification Based on Mel Frequency Cepstral Coefficient Feature Extraction Using Self-Organized Maps and Radial Basis FunctionAsrivatun Nikmah0Auli Damayanti1Edi Winarko2Universitas AirlanggaUniversitas AirlanggaUniversitas AirlanggaSpeech recognition is one of the most popular research fields, one of which is about emotion identification. Voice-based emotion identification is carried out to determine the pattern of emotions using the depth analysis mechanism of voice signal development and feature extraction that carries the emotional characteristic parameters of the speaker's voice. Furthermore, the emotional characteristics of the speaker's voice are classified using an artificial neural network method to recognize patterns. In this study, emotion identification from voice signal data is classified into angry, sad, happy, and neutral emotions. The stages of voice-based emotion identification, including the feature extraction stage using the mel frequency cepstral coefficient, produce coefficient values, which will be used in the identification stage using the Self Organized Maps method on the Radial Basis Function.https://e-journal.unair.ac.id/CONMATHA/article/view/68246 |
| spellingShingle | Asrivatun Nikmah Auli Damayanti Edi Winarko Voice-Based Emotion Identification Based on Mel Frequency Cepstral Coefficient Feature Extraction Using Self-Organized Maps and Radial Basis Function Contemporary Mathematics and Applications (ConMathA) |
| title | Voice-Based Emotion Identification Based on Mel Frequency Cepstral Coefficient Feature Extraction Using Self-Organized Maps and Radial Basis Function |
| title_full | Voice-Based Emotion Identification Based on Mel Frequency Cepstral Coefficient Feature Extraction Using Self-Organized Maps and Radial Basis Function |
| title_fullStr | Voice-Based Emotion Identification Based on Mel Frequency Cepstral Coefficient Feature Extraction Using Self-Organized Maps and Radial Basis Function |
| title_full_unstemmed | Voice-Based Emotion Identification Based on Mel Frequency Cepstral Coefficient Feature Extraction Using Self-Organized Maps and Radial Basis Function |
| title_short | Voice-Based Emotion Identification Based on Mel Frequency Cepstral Coefficient Feature Extraction Using Self-Organized Maps and Radial Basis Function |
| title_sort | voice based emotion identification based on mel frequency cepstral coefficient feature extraction using self organized maps and radial basis function |
| url | https://e-journal.unair.ac.id/CONMATHA/article/view/68246 |
| work_keys_str_mv | AT asrivatunnikmah voicebasedemotionidentificationbasedonmelfrequencycepstralcoefficientfeatureextractionusingselforganizedmapsandradialbasisfunction AT aulidamayanti voicebasedemotionidentificationbasedonmelfrequencycepstralcoefficientfeatureextractionusingselforganizedmapsandradialbasisfunction AT ediwinarko voicebasedemotionidentificationbasedonmelfrequencycepstralcoefficientfeatureextractionusingselforganizedmapsandradialbasisfunction |