131 research outputs found
Pop Music Highlighter: Marking the Emotion Keypoints
The goal of music highlight extraction is to get a short consecutive segment
of a piece of music that provides an effective representation of the whole
piece. In a previous work, we introduced an attention-based convolutional
recurrent neural network that uses music emotion classification as a surrogate
task for music highlight extraction, for Pop songs. The rationale behind that
approach is that the highlight of a song is usually the most emotional part.
This paper extends our previous work in the following two aspects. First,
methodology-wise we experiment with a new architecture that does not need any
recurrent layers, making the training process faster. Moreover, we compare a
late-fusion variant and an early-fusion variant to study which one better
exploits the attention mechanism. Second, we conduct and report an extensive
set of experiments comparing the proposed attention-based methods against a
heuristic energy-based method, a structural repetition-based method, and a few
other simple feature-based methods for this task. Due to the lack of
public-domain labeled data for highlight extraction, following our previous
work we use the RWC POP 100-song data set to evaluate how the detected
highlights overlap with any chorus sections of the songs. The experiments
demonstrate the effectiveness of our methods over competing methods. For
reproducibility, we open source the code and pre-trained model at
https://github.com/remyhuang/pop-music-highlighter/.Comment: Transactions of the ISMIR vol. 1, no.
Multiple scale music segmentation using rhythm, timbre and harmony
The segmentation of music into intro-chorus-verse-outro, and similar segments, is a difficult topic. A method for performing automatic segmentation based on features related to rhythm, timbre, and harmony is presented, and compared, between the features and between the features and manual segmentation of a database of 48 songs. Standard information retrieval performance measures are used in the comparison, and it is shown that the timbre-related feature performs best.</p
Score-Informed Source Separation for Musical Audio Recordings [An overview]
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IDENTIFICATION OF COVER SONGS USING INFORMATION THEORETIC MEASURES OF SIMILARITY
13 pages, 5 figures, 4 tables. v3: Accepted version13 pages, 5 figures, 4 tables. v3: Accepted version13 pages, 5 figures, 4 tables. v3: Accepted versio
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