Ambient Music Tracks with BPM and Mood Metadata

10 professional ambient music tracks in WAV format optimized for AI/ML training. Each track includes metadata such as BPM, key, mood, duration, and instrumentation. The dataset was created by Pthe-67 and last updated on Hugging Face in April 2026.

Use Cases

• Train music generation models based on high-quality ambient audio tracks.
• Develop mood classification algorithms using the provided mood metadata.
• Analyze musical structure and tempo using the BPM and key metadata.
• Benchmark audio processing and feature extraction techniques on clean, artifact-free recordings.

Strengths

• 10 professionally recorded ambient tracks provide a focused collection.
• Audio files are high-fidelity WAV format at 48kHz and 24-bit depth.
• Each track includes structured metadata (BPM, key, mood, duration, instrumentation).
• Recordings are described as clean, artifact-free, and with flat EQ for minimal frequency coloring.

Limitations

• The dataset contains only 10 tracks, which is a small sample size.
• Row count and total dataset size are unknown, limiting suitability assessment.
• Column-level documentation is absent; field semantics must be inferred from the provided CSV/TXT files.

Provenance

Source

Pthe-67 on Hugging Face.

Freshness

Last updated 2026-04-16 16:45:33.