CTC-SRS02 Audio AI Transcription System
Overview
- Utilizes AI + industry-grade intelligent engine
- Performs real-time or offline speech transcription
- Supports advanced features such as automatic number formatting, punctuation prediction, and endpoint detection
- Accurately recognizes call content in noisy environments and with various accents
- Generates text for retrieval, keyword detection, and post-analysis
Key Features
High Recognition Accuracy
- Maintains high accuracy even under complex noise conditions, capable of distinguishing various accents and industry-specific terms
Speaker Separation
- Automatically differentiates between "agent speech" and "caller speech" to facilitate subsequent analysis
Custom Hotwords
- Allows uploading of specialized terminology for specific scenarios to optimize recognition performance
Language Model Reconfiguration
- Utilizes deep learning with patch-based optimization to ensure accuracy in scenarios with complex accents
Core Parameters
- Supported Languages: Chinese, English, customizable for multiple languages
- Transcription Method: Real-time / Offline
- Interface: RESTful / WebSocket API, compatible with recording management or softswitch systems
- Hardware Requirements: GPU/high-performance server recommended for large-scale concurrent inference
- Recognition Accuracy: 85~95% in real industrial environments (varies with noise/accent)
Typical Applications
- Dispatch/Emergency Calls: Real-time transcription of instructions and archiving for post-event review;
- Industrial Customer Hotline: Automatic text recording to enhance operational efficiency;
- Security Monitoring: Detection of sensitive keywords in calls to trigger alerts or categorized analysis.