dvcrn 🎵 Song Recognition
Recognize songs by singing, or audio file using iFlytek's advanced Query By ACRCloud technology.
Designed for music identification, song discovery, and audio recognition scenarios.
✨ Features
- Singing recognition
- Audio file recognition
- High-accuracy song matching
- Real-time synchronous detection
- Multiple audio format support
- URL and file path input support
🚀 Usage
Using audio file path:
python {baseDir}/scripts/index.py "<audio_path>"
Examples:
python {baseDir}/scripts/index.py "humming.wav"
📋 Input Specification
Audio Requirements
- Supported formats: MP3
- Sample rate: 16000Hz
- Audio encoding: lame
- Duration: 5-30 seconds recommended
- singing melody
⚠ Constraints
- Audio must contain clear melody
- API credentials must be configured
- Network connection required
- Synchronous processing - instant results
- Audio quality affects recognition accuracy
🔧 Environment Setup
Required:
- Python available in PATH
- Environment variables configured:
export XF_SONG_APP_ID=your_app_id
export XF_SONG_API_KEY=your_api_key
export XF_SONG_API_SECRET=your_api_secret
Or configure it in ~/.openclaw/openclaw.json:
{
"env": {
"XF_SONG_APP_ID": "your_app_id",
"XF_SONG_API_KEY": "your_api_key",
"XF_SONG_API_SECRET": "your_api_secret"
}
}
📦 Output
Returns JSON response with:
- Song name
- Artist name
- Album information
- Confidence score
- Match details
🎯 Target Use Cases
- Music identification apps
- Song discovery platforms
- Karaoke applications
- Music education tools
- Audio content recognition
- Copyright detection
- Music search engines
🛠 Extensibility
Future enhancements may include:
- Batch audio processing
- Real-time streaming recognition
- Custom music library
- Multi-language song support
- Genre classification
Built for automation workflows and AI-driven music recognition.