README.md

metadata

title: Audio Mood Classifier
emoji: 🎵
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 5.33.0
app_file: app.py
pinned: false
fullWidth: false
license: apache-2.0
short_description: Classify the mood of an uploaded song
suggested_hardware: zero-a10g
startup_duration_timeout: 45m
preload_from_hub:
  - guyPerry/audio-mood-classifier
models:
  - guyPerry/audio-mood-classifier

🎵 Audio Mood Classifier 🎵

Can a machine feel the mood of a song?

Upload any song (MP3) and get an instant mood prediction from a fine-tuned deep learning model — no lyrics, no metadata, just the raw audio.

The model is a fine-tuned Audio Spectrogram Transformer (AST) pre-trained by MIT on AudioSet. Because mood is inherently subjective, it targets broad emotional character rather than precise genre.

Links: Model card · Project on GitHub

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How this demo works

For each upload, the app:

1. Skips the first and last 30 seconds of the track (to avoid intros and outros).
2. Extracts 3 evenly-spaced clips, 10 seconds each, from the remaining audio.
3. Resamples to 16 kHz mono and applies EBU R128 loudness normalization (−20 LUFS), matching the training pipeline.
4. Classifies each clip independently, then combines the confidence scores (late fusion) into one final prediction.

Training used 6 segments per song; the demo uses 3 for a faster response while keeping the same sampling logic.

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Training dataset

The model was trained on a custom dataset built from scratch — a hand-curated catalog matched against a personal music library. Each song was manually assigned to one mood category.

Total songs	250
Mood categories	3
Segments per song (training)	6
Segment length	10 seconds
Guard buffer	30 s skipped at each end of every track
Total training segments	up to 1,500 (250 songs × 6 segments)
Audio preprocessing	16 kHz mono · EBU R128 loudness norm (−20 LUFS)
Train / eval / test split	~70% / 15% / 15% (group-aware — all segments from the same song stay in the same split)

Songs per category

Category	Songs in catalog
🌧 calm_melancholic	84
😐 moderate_neutral	74
⚡ energetic_upbeat	90
Total	250

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Mood classes

Label	Description
🌧 calm_melancholic	Slow, introspective, melancholic
😐 moderate_neutral	Balanced, mid-energy, neutral feel
⚡ energetic_upbeat	Fast, high-energy, upbeat