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The dataset is publically available to the research community, which is foremost intended for benchmarking in music emotion retrieval and recognition. To straightforwardly evaluate the methodologies for music affective analysis, it also involves pre-computed audio feature sets.
We present the PMEmo dataset containing emotion annotations of 794 songs as well as the simultaneous electrodermal activity (EDA) signals.
A Multimodal Framework for Large-Scale Emotion Recognition by Fusing Music and Electrodermal Activity Signals · Computer Science. ACM Trans. Multim. Comput.
... The PMEmo dataset [13] consists of 794 popular music choruses, with 767 annotated with static emotion labels in terms of arousal and valence. It is designed ...
The dataset is publically available to the research community, which is foremost intended for benchmarking in music emotion retrieval and recognition. To ...
Aug 3, 2020 · PMEmo Datase PMEmo is the currently largest dataset[13] with EDA and music signals for emotion recognition. This dataset extracted chorus parts ...
Description and music styles: The dataset contains 400 excerpts collected from Western classical music recordings and 400 excerpts collected from Chinese ...
In this work, we investigate the use of sentiment analysis on online social media conversations as an alternate data source to train computa- tional models to ...
PMEmo: A Dataset For Music Emotion Computing. GitHub Page. The PMEmo dataset [1] was initially comprised of 794 music chorus clips from several western ...
Jun 28, 2022 · Kejun Zhang, Hui Zhang, Simeng Li, Chang-yuan Yang, Lingyun Sun: The PMEmo Dataset for Music Emotion Recognition. ICMR 2018: 135-142.
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