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Studying the ways to recommend music to a user is a central task within the music information research community. From a content-based point of view, this task can be regarded as obtaining a suitable distance measurement between songs defined on a certain feature space. We propose two such distance measures. First, a low-level measure based on tempo-related aspects, and second, a high-level semantic...
A robust and efficient technique for automatic music mood annotation is presented. A song's mood is expressed by a supervised machine learning approach based on musical features extracted from the raw audio signal. A ground truth, used for training, is created using both social network information systems and individual experts. Tests of 7 different classification configurations have been performed,...
Nowadays, the term cover song (or simply cover) can mean any new version, performance, rendition, or recording of a previously recorded track. Cover song identification is a task that has received increased popularity in the Music Information Retrieval (MIR) community in recent years, as it provides a direct and objective way for evaluating music similarity. In this paper, we propose a new method...
We present a new technique for audio signal comparison based on tonal subsequence alignment and its application to detect cover versions (i.e., different performances of the same underlying musical piece). Cover song identification is a task whose popularity has increased in the music information retrieval (MIR) community along in the past, as it provides a direct and objective way to evaluate music...
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