Publicação
Automatic Acoustic Scene Classification
| Resumo: | This paper presents a baseline system for automatic acoustic scene classification based on the audio signals alone. The proposed method is derived from classic, content-based, music classification approaches, and consists in a feature extraction phase followed by two dimensionality reduction steps (PCA and LDA) and a classification phase done using a k nearest-neighbors algorithm.This paper also reports on how our system performed in the context of the DCASE 2016 challenge, for the acoustic scene classification task. |
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| Autores principais: | Marques, Gonçalo Caetano |
| Outros Autores: | Langlois, Thibault |
| Assunto: | Multimedia Machine Learning, Music Information Retrieval |
| Ano: | 2017 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | unknown |
| Instituição associada: | Instituto Superior de Engenharia de Lisboa |
| Idioma: | inglês |
| Origem: | i-ETC : ISEL Academic Journal of Electronics Telecommunications and Computers |
| Resumo: | This paper presents a baseline system for automatic acoustic scene classification based on the audio signals alone. The proposed method is derived from classic, content-based, music classification approaches, and consists in a feature extraction phase followed by two dimensionality reduction steps (PCA and LDA) and a classification phase done using a k nearest-neighbors algorithm.This paper also reports on how our system performed in the context of the DCASE 2016 challenge, for the acoustic scene classification task. |
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