Identificación automática de eventos sonoros de música y tráfico en grabaciones en ambientes controlados mediante descriptores de audio y el algoritmo de clasificación de máquinas de vectores de soporte (SVM)
Audio content analysis of real world recordings instead of common SPL measures is proposed as a technique for environmental noise evaluation. However, because of the large quantity of data that a monitoring system produces an automatic sound event algorithm was built using audio descriptors as MFCC,...
| Autor Principal: | Giraldo Valencia, José Omar |
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| Formato: | info:eu-repo/semantics/bachelorThesis |
| Idioma: | spa |
| Publicado: |
Ingenierias
2017
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| Acceso en línea: |
[1] J. O. Giraldo Valencia, “Identificación automática de eventos sonoros de música y tráfico en grabaciones en ambientes controlados mediante descriptores de audio y el algoritmo de clasificación de máquinas de vectores de soporte(SVM).”, Trabajo de grado Ingeniería de Sonido, Universidad de San Buenaventura Medellín, Facultad de Ingenierías, 2017. |
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| Sumario: |
Audio content analysis of real world recordings instead of common SPL measures is proposed as a technique for environmental noise evaluation. However, because of the large quantity of data that a monitoring system produces an automatic sound event algorithm was built using audio descriptors as MFCC, spectral centroid, zcr and roll off coupled with a supervised learning approach with SVM. For traffic related audio events an 84% recognition rate was achieved and for music related events a 95% rate in controlled environments. This was done in database composed of outdoor residential audios recorded in Medellin city. |
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