Título:
Toward interpretable polyphonic sound event detection with attention maps based on local prototypes
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Autor:
Zinemanas, Pablo
Rocamora, Martín
Fonseca, Eduardo
Font, Frederic
Serra, Xavier
Rocamora, Martín
Fonseca, Eduardo
Font, Frederic
Serra, Xavier
Tutor:
Tipo de documento:
Ponencia
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Palabras clave:
Interpretability
Sound event detection
Prototypes
Sound event detection
Prototypes
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Año de publicación:
2021
Contenido:
Resumen:
Understanding the reasons behind the predictions of deep neural networks is a pressing concern as it can be critical in several application scenarios. In this work, we present a novel interpretable model for polyphonic sound event detection. It tackles one of the limitations of our previous work, i.e. the difficulty to deal with a multi-label setting properly. The proposed architecture incorporates a prototype layer and an attention mechanism. The network learns a set of local prototypes in the latent space representing a patch in the input representation. Besides, it learns attention maps for positioning the local prototypes and reconstructing the latent space. Then, the predictions are solely based on the attention maps. Thus, the explanations provided are the attention maps and the corresponding local prototypes. Moreover, one can reconstruct the prototypes to the audio domain for inspection. The obtained results in urban sound event detection are comparable to that of two opaque baselines but with fewer parameters while offering interpretability.
Descripción:
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Editorial:
Universitat Pompeu Fabra
EN:
6th Workshop on Detection and Classification of Acoustic Scenes and Events, DCASE 2021, Barcelona, Spain, 15-19 nov. 2021, pp. 50-54.
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Citación:
Zinemanas, P., Rocamora, M., Fonseca, E. y otros. Toward interpretable polyphonic sound event detection with attention maps based on local prototypes [en línea]. EN: 6th Workshop on Detection and Classification of Acoustic Scenes and Events, DCASE 2021, Barcelona, Spain, 15-19 nov. 2021, pp. 50-54.
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Departamento académico:
Procesamiento de Señales
Grupo de investigación:
Procesamiento de Audio
Licencia:
Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
Colecciones:
| Ficheros | Descripción | Tamaño | Formato | ||
|---|---|---|---|---|---|
| ZRFFS21.pdf | Versión publicada | 723.73 KB | Adobe PDF |