A linear iteration time layout algorithm for visualising high-dimensional data
Proceedings of the 7th conference on Visualization '96
Combining Pattern Classifiers: Methods and Algorithms
Combining Pattern Classifiers: Methods and Algorithms
Inferring similarity between music objects with application to playlist generation
Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval
Incorporating machine-learning into music similarity estimation
Proceedings of the 1st ACM workshop on Audio and music computing multimedia
A hybrid social-acoustic recommendation system for popular music
Proceedings of the 2007 ACM conference on Recommender systems
Dynamic visualization of music classification systems
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Incorporating cultural representations of features into audio music similarity estimation
IEEE Transactions on Audio, Speech, and Language Processing
Neural network classification of gunshots using spectral characteristics
ACMOS'11 Proceedings of the 13th WSEAS international conference on Automatic control, modelling & simulation
Information Processing and Management: an International Journal
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Several authors have presented systems that estimate the audio similarity of two pieces of music through the calculation of a distance metric, such as the Euclidean distance, between spectral features calculated from the audio, related to the timbre or pitch of the signal. These features can be augmented with other, temporally or rhythmically based features such as zero-crossing rates, beat histograms, or fluctuation patterns to form a more well-rounded music similarity function. It is our contention that perceptual or cultural labels, such as the genre, style, or emotion of the music, are also very important features in the perception of music. These labels help to define complex regions of similarity within the available feature spaces.We demonstrate a machine-learning-based approach to the construction of a similarity metric, which uses this contextual information to project the calculated features into an intermediate space where a music similarity function that incorporates some of the cultural information may be calculated.