| Revista: | Computación y sistemas |
| Base de datos: | |
| Número de sistema: | 000560811 |
| ISSN: | 1405-5546 |
| Autores: | Martínez Navarro, José Angel1 Rubio Espino, Elsa1 Sossa Azuela, Juan Humberto1 Ponce Ponce, Víctor Hugo1 Molina Lozano, Herón1 García Sebastián, Luis Martín1 |
| Instituciones: | 1Instituto Politécnico Nacional, Centro de Investigación en Computación, México |
| Año: | 2023 |
| Periodo: | Jul-Sep |
| Volumen: | 27 |
| Número: | 3 |
| Paginación: | 653-665 |
| País: | México |
| Idioma: | Inglés |
| Resumen en inglés | This article presents the findings of a bio-inspired audio emotion-detection system and compares its performance with various neural network approaches, namely spiking neural networks, convolutional neural networks, and multilayer perceptrons. The simulation results demonstrate the effectiveness of the proposed approach in accurately detecting audio emotions. Additionally, the detection task can achieve even higher levels of precision by improving the training methods. The research utilizes the EmoDB, SAVEE, and RAVDESS databases. |
| Keyword: | SNN, DNN, MLP, Emotion recognition, Encoding |
| Texto completo: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
