Vocal Music Tracks
Our Vocal Music dataset is composed of 32,500 tracks, perfect for developing voice recognition, speech synthesis, and emotion detection applications, this dataset offers an extensive collection of vocal tracks, ensuring comprehensive training for diverse audio AI projects.
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Leverage this dataset for:
- Music Recommendation Systems: Enhance personalized music streaming services by developing advanced recommendation algorithms that suggest songs based on user preferences, listening history, and metadata like mood, style, BPM, and key.
This dataset is ideal for
- Automatic Music Classification and Tagging: Improve music library organization and searchability by training AI models to classify and tag songs automatically with metadata such as style, mood, intensity, and project, ensuring accurate and consistent categorization.
- Music Composition and Arrangement: Assist composers and producers in creating new music by using AI to analyze existing tracks and generate new compositions or arrangements that match specific styles, moods, BPM, and keys, providing creative suggestions and inspirations.
- Sentiment and Emotion Analysis: Understand and respond to listener emotional responses by developing AI models to analyze lyrics, mood, and intensity to gauge the emotional impact of songs, which can be used to create emotionally resonant playlists or to study trends in music and listener behavior.
Technical Specifications
- Type: Audio
- Quantity: 32,500 tracks
- Domain: Music
- Data Type: Simulated
- Metadata: Filename Full Version, Cue ID, Song Name, Album, Composer, Artist, Publisher, Description, Lyrics, Mood, Project, Style (Higher Level), Style (Lower Level), BPM, Key, Intensity, Time Signature (Please note that metadata may vary between datasets.)
- File Format: WAV, FLAC
- Sample Rate: 41kHz, 48 kHz
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