Utilize este identificador para referenciar este registo:
https://hdl.handle.net/10316/94384
Título: | Music Emotion Recognition with Standard and Melodic Audio Features | Autor: | Panda, Renato Rocha, Bruno Paiva, Rui Pedro |
Palavras-chave: | Music emotion recognition; Melody; Melodic audio features | Data: | 2015 | Editora: | Taylor & Francis | Projeto: | RECARDI (QREN 22997) info:eu-repo/grantAgreement/FCT/5876-PPCDTI/102185/PT/MOODetector - A System for Mood-based Classification and Retrieval of Audio Music info:eu-repo/grantAgreement/FCT/SFRH/SFRH/BD/91523/2012/PT/EMOTION-BASED ANALYSIS AND CLASSIFICATION OF AUDIO MUSIC |
Título da revista, periódico, livro ou evento: | Applied Artificial Intelligence (AAI) | Volume: | 29 | Número: | 4 | Resumo: | We propose a novel approach to music emotion recognition by combining standard and melodic features extracted directly from audio. To this end, a new audio dataset organized similarly to the one used in MIREX mood task comparison was created. From the data, 253 standard and 98 melodic features are extracted and used with several supervised learning techniques. Results show that, generally, melodic features perform better than standard audio. The best result, 64% f-measure, with only 11 features (9 melodic and 2 standard), was obtained with ReliefF feature selection and Support Vector Machines. | URI: | https://hdl.handle.net/10316/94384 | ISSN: | 0883-9514 1087-6545 |
DOI: | 10.1080/08839514.2015.1016389 | Direitos: | embargoedAccess |
Aparece nas coleções: | I&D CISUC - Artigos em Revistas Internacionais |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
---|---|---|---|---|
Panda, Rocha, Paiva - 2015 - Music Emotion Recognition with Standard and Melodic Audio Features [Accepted Manuscript].pdf | Accepted Manuscript | 801.27 kB | Adobe PDF | Ver/Abrir |
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