{
  "$type": "site.standard.document",
  "bskyPostRef": {
    "cid": "bafyreicayefouojnkfmufajh4ljewkjlzofwcbtwmdoe7nza6krpt64boe",
    "uri": "at://did:plc:pgryn3ephfd2xgft23qokfzt/app.bsky.feed.post/3mok6q7fo2432"
  },
  "path": "/t/enigma-sound-multi-modal-emotion-to-music-architecture-layout-gradio-cnn-lstm-walkthrough/176936#post_1",
  "publishedAt": "2026-06-18T05:24:24.000Z",
  "site": "https://discuss.huggingface.co",
  "tags": [
    "Enigma Sound Ai - a Hugging Face Space by ApurvaDev111"
  ],
  "textContent": "Hey everyone,\n\nI wanted to share a UI case study layout I put together for a research project mapping text, vocal frequencies (Bi-LSTM), and facial micro-expressions (CNN) into dynamic audio layers via Music21.\n\nBecause the underlying models are too heavy for basic free tiers, I built a lightweight Gradio interface to act as a 0-click visual production walkthrough and tech-stack overview.\n\nWould love any feedback on the layout structure or optimization tips for multi-stream pipelines!\n\nLink: Enigma Sound Ai - a Hugging Face Space by ApurvaDev111",
  "title": "Enigma Sound : Multi-Modal Emotion-to-Music Architecture Layout (Gradio + CNN/LSTM Walkthrough)"
}