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MML Classification of Music Genres
2003Inference of musical genre, whilst seemingly innate to the human mind, remains a challenging task for the machine learning community. Online music retrieval and automatic music generation are just two of many interesting applications that could benefit from such research.
Adrian C. Bickerstaffe, Enes Makalic
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Music Genre Classification with Transformer Classifier
Proceedings of the 2020 4th International Conference on Digital Signal Processing, 2020Music Genre Classification is a significant and practical field of Music Information Retrieval. Deep learning is increasingly being applied to Music Genre Classification for two main reasons. Firstly, it avoids the manual selection of audio signal features.
Yingying Zhuang +2 more
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Genre classification of music by tonal harmony
Intelligent Data Analysis, 2010In this paper we present a genre classification framework for audio music based on a symbolic classification system. Audio signals are transformed into a symbolic representation of harmony using a chord transcription algorithm, based on the computation of harmonic pitch class profiles.
Carlos Pérez-Sancho +5 more
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Text genre classification with genre-revealing and subject-revealing features
Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval, 2002Subject or prepositional content has been the focus of most classification research. Genre or style, on the other hand, is a different and important property of text, and automatic text genre classification is becoming important for classification and retrieval purposes as well as for some natural language processing research. In this paper, we present
Yong-Bae Lee, Sung-Hyon Myaeng
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Automatic Classification of Musical Genres Using Inter-Genre Similarity
IEEE Signal Processing Letters, 2007Musical genre classification is an essential tool for music information retrieval systems and it has potential to become a highly demanded application in various media platforms. Two important problems of the automatic musical genre classification are feature extraction and classifier design. In this letter, we propose two novel classifiers using inter-
Ulas Bagci, Engin Erzin
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Video genre classification using dynamics
2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221), 2002The problem addressed here is the classification of videos at the highest level into pre-defined genre. The approach adopted is based on the dynamic content of short sequences (/spl sim/30 secs). This paper presents two methods of extracting motion from a video sequence: foreground object motion and background camera motion.
Matt J. Roach +2 more
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Detecting Musical Genre Borders for Multi-label Genre Classification
2013 IEEE International Symposium on Multimedia, 2013In this paper, we propose a novel method to detect music genre borders for the music genre classification. The music genre classification is getting more important because music is influenced by an increasing amount of different musical styles. A general approach to classify music genres is a single genre labeling that usually gives the meaning of ...
Hiroki Nakamura +2 more
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Genre classification of symbolic pieces of music
Journal of Intelligent Information Systems, 2016Automatic classification of music is a complex and interesting research problem due to the difficulties that arise when determining the musical features that should be considered for classification and the characteristics that define each particular genre.
Marcelo Gabriel Armentano +2 more
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Genre classification of symbolic music with SMBGT
Proceedings of the 6th International Conference on PErvasive Technologies Related to Assistive Environments, 2013Automatic music genre classification is a task that has attracted the interest of the music community for more than two decades. Music can be of high importance within the area of assistive technologies as it can be seen as an assistive technology with high therapeutic and educational functionality for children and adults with disabilities.
Kotsifakos, Alexios +4 more
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Reinardus. Yearbook of the International Reynard Society, 2000
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