rs3gw 0.2.1

High-Performance AI/HPC Object Storage Gateway powered by scirs2-io
{
  "id": "audio-feature-extraction",
  "name": "Audio Feature Extraction",
  "version": "1.0.0",
  "description": "Extract audio features (spectrograms, MFCCs) for speech recognition and audio classification",
  "steps": [
    {
      "id": "extract_features",
      "step_type": "audio_features",
      "config": {
        "feature_type": "mel_spectrogram",
        "sample_rate": 16000,
        "n_fft": 2048,
        "hop_length": 512,
        "n_mels": 128,
        "f_min": 0.0,
        "f_max": 8000.0,
        "normalize": true
      },
      "cache_results": true,
      "description": "Extract Mel spectrogram features from audio"
    }
  ],
  "metadata": {
    "created_at": "2025-12-31T00:00:00Z",
    "author": "audio-ml-team",
    "target_model": "Wav2Vec2/Whisper/Audio Classifier",
    "dataset": "LibriSpeech/AudioSet",
    "use_case": "Speech recognition and audio classification",
    "recommended_batch_size": 16,
    "notes": "Optimized for speech and audio understanding tasks"
  }
}