2022
DOI: 10.1007/s11042-021-11584-7
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End-to-end music emotion variation detection using iteratively reconstructed deep features

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Cited by 17 publications
(8 citation statements)
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“…Among them, the blind separation of speech and music signals is a main research direction of blind source separation technology. A basic preprocessing method plays a very important role in the research of speech and music signal processing [2][3][4][5].…”
Section: Introductionmentioning
confidence: 99%
“…Among them, the blind separation of speech and music signals is a main research direction of blind source separation technology. A basic preprocessing method plays a very important role in the research of speech and music signal processing [2][3][4][5].…”
Section: Introductionmentioning
confidence: 99%
“…In this way, all emotions can be represented using these two dimensions of V and A. The Lakh-Spotify Dataset [ 23 ] is one of the latest datasets that uses symbolic music paired with emotion labels in terms of VA. Valence and Arousal labels have also been used for tasks such as controlling emotion in generated music [ 24 , 25 , 26 , 27 ] as well as variation detection in emotion from music [ 28 ]. Due to the nature of the two representations, MER techniques for analyzing categorical annotations usually involve classification, while dimensional annotations require regression techniques.…”
Section: Related Workmentioning
confidence: 99%
“…In general, both LSTM and GRU can use the gate function to retain the required data, so as to ensure that no information is lost. In addition, LSTM has a more complex structure and more parameters than GRU, so the overall learning rate of GRU is higher than that of LSTM [14].…”
Section: Gated Recurrent Unit (Gru)mentioning
confidence: 99%