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Music Emotion Recognition

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크
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평가표
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보존된 평가 기록
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데이터셋

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RAVDESS

The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) contains 7,356 files (total size: 24.8 GB). The database contains 24 professional actors (12 female, 12 male), vocalizing two lexically-matched statements in a neutral North American accent. Speech includes calm, happy, sad, angry, fearful, surprise, and disgust expressions, and song contains calm, happy, sad, angry, and fearful emotions. Each expression is produced at two levels of emotional intensity (normal, strong), with an additional neutral expression. All conditions are available in three modality formats: Audio-only (16bit, 48kHz .wav), Audio-Video (720p H.264, AAC 48kHz, .mp4), and Video-only (no sound). Note, there are no song files for Actor_18. Paper: The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS): A dynamic, multimodal set of facial and vocal expressions in North American English Source:

VGMIDI

VGMIDI is a dataset of piano arrangements of video game soundtracks. It contains 200 MIDI pieces labeled according to emotion and 3,850 unlabeled pieces. Each labeled piece was annotated by 30 human subjects according to the Circumplex (valence-arousal) model of emotion using a custom [web tool](https://github.com/lucasnfe/adl-music annotation).

PIAST

Click to add a brief description of the dataset (Markdown and LaTeX enabled). Provide: * a high-level explanation of the dataset characteristics * explain motivations and summary of its content * potential use cases of the dataset

XMIDI

XMIDI is a comprehensive, large-scale symbolic music dataset that includes accurate emotion and genre labels, consisting of 108,023 MIDI files. The average duration of the music pieces is approximately 176 seconds, yielding a total dataset length of around 5,278 hours.

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