🎵 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.