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Transfer learning from speech to music: towards language-sensitive emotion recognition models ...
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Transfer learning from speech to music: towards language-sensitive emotion recognition models ...
Abstract: In this study, we address emotion recognition using unsupervised feature learning from speech data, and test its transferability to music. Our approach is to pre-train models using speech in English and Mandarin, and then fine-tune them with excerpts of music labeled with categories of emotion. Our initial hypothesis is that features automatically learned from speech should be transferable to music. Namely, we expect the intra-linguistic setting (e.g., pre-training on speech in English and fine-tuning on music in English) should result in improved performance over the cross-linguistic setting (e.g., pre-training on speech in English and fine-tuning on music in Mandarin). Our results confirm previous research on cross-domain transferability, and encourage research towards language-sensitive Music Emotion Recognition (MER) models. ...
Keyword: multi-task learning; music emotion recognition; sparse convolutional autoencoder; speech emotion recognition; unsupervised learning
URL: https://zenodo.org/record/4076791
https://dx.doi.org/10.5281/zenodo.4076791
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Factors In Human Recognition Of Timbre Lexicons Generated By Data Clustering ...
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Factors In Human Recognition Of Timbre Lexicons Generated By Data Clustering ...
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5
What/when causal expectation modelling applied to audio signals
In: Connection science. - Abingdon, Oxfordshire : Taylor & Francis 21 (2009) 2, 119-143
OLC Linguistik
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6
What/when causal expectation modelling applied to audio signals
In: Connection science. - Abingdon, Oxfordshire : Taylor & Francis 21 (2009) 2, 119-144
OLC Linguistik
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7
Chroma binary similarity and local alignment applied to cover song identification
In: Institute of Electrical and Electronics Engineers. IEEE transactions on audio, speech and language processing. - New York, NY : Inst. 16 (2008) 6, 1138-1151
BLLDB
OLC Linguistik
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