System Overview
The Call Center Audit System is a comprehensive web-based application designed to analyze and evaluate call center conversations using advanced AI technologies including Whisper for speech recognition and NLP for sentiment analysis.
🎯 Smart Transcription
Automatically convert audio calls to text using OpenAI's Whisper with high accuracy across multiple languages.
🔍 Advanced Analysis
Perform sentiment analysis, emotion detection, and entity recognition using Natural Language Processing.
📊 Quality Scoring
Generate comprehensive quality scores based on professionalism, empathy, clarity, and efficiency metrics.
📈 Real-time Analytics
Monitor call center performance with detailed reports and interactive dashboards.
System Architecture
| Component | Technology | Purpose |
|---|---|---|
| Frontend | PHP, HTML, CSS, JavaScript | User interface and interaction |
| Backend | PHP, MySQL | Business logic and data storage |
| Speech Recognition | OpenAI Whisper | Audio to text conversion |
| NLP Analysis | Python, NLTK, spaCy, TextBlob | Text analysis and insights |
| Audio Processing | FFmpeg, Sox | Audio file manipulation |
🚀 Getting Started
System Requirements
- Web Browser: Chrome 90+, Firefox 88+, Safari 14+
- Internet Connection: Required for initial setup
- Audio Files: WAV, MP3, or OGG format
- File Size: Maximum 100MB per audio file
First Time Login
Open your web browser and navigate to your system URL (e.g., http://your-server.com/)
Use the default administrator account:
Password: password
Immediately change your password after first login for security.
Familiarize yourself with the main dashboard and navigation menu.
👥 User Roles & Permissions
| Role | Permissions | Access Level |
|---|---|---|
| Administrator |
|
Complete |
| Supervisor |
|
Managerial |
| Agent |
|
Limited |
Role Management
Administrators can manage user roles through the User Management section:
✨ Key Features
📁 Call Upload & Management
Easily upload and manage call recordings with automatic processing and analysis.
- Call date and time
- Customer details (phone, name)
- Call category (sales, support, complaint, etc.)
🎤 Speech-to-Text & Analysis
Advanced AI-powered transcription and analysis using Whisper and NLP technologies.
Analysis Components:
Sentiment Analysis
Detect positive, negative, or neutral sentiment with polarity scores
Emotion Detection
Identify emotions like happiness, anger, sadness, fear, and surprise
Entity Recognition
Extract names, organizations, locations, and other entities
Topic Modeling
Identify key topics and themes discussed in the conversation
🔑 Keyword Monitoring
Monitor specific keywords and phrases across all call recordings.
Managing Keywords:
- Keyword phrase
- Category (positive, negative, complaint, etc.)
- Severity level (low, medium, high)
Keyword Categories:
| Category | Purpose | Example Keywords |
|---|---|---|
| Positive | Customer satisfaction indicators | thank you, great, excellent, happy |
| Negative | Customer dissatisfaction indicators | angry, terrible, worst, hate |
| Complaint | Formal complaint indicators | refund, escalate, manager, supervisor |
| Sales | Sales-related terminology | discount, price, sale, buy |
| Support | Technical support terms | help, problem, fix, solution |
⭐ Quality Evaluation
Comprehensive quality assessment with automated scoring and manual evaluations.
Automated Quality Metrics:
Professionalism Score
Measures use of professional language and courtesy
Empathy Score
Evaluates understanding and consideration of customer feelings
Clarity Score
Assesses communication clarity and understandability
Efficiency Score
Measures call handling efficiency and resolution
Manual Evaluation Process:
📈 Reports & Analytics
Comprehensive reporting and analytics for performance monitoring.
Available Reports:
| Report Type | Description | Access Level |
|---|---|---|
| Call Volume Analysis | Daily/weekly/monthly call statistics | All Roles |
| Agent Performance | Individual agent quality scores and metrics | Supervisor+ |
| Keyword Trends | Keyword occurrence patterns over time | Supervisor+ |
| Sentiment Analysis | Customer sentiment trends and patterns | Supervisor+ |
| Quality Scorecard | Comprehensive quality assessment reports | Supervisor+ |
Export Options:
- PDF Reports: For formal presentations and documentation
- Excel Export: For data analysis and further processing
- CSV Data: For integration with other systems
📝 Step-by-Step Guides
Complete Call Processing Workflow
Navigate to Upload Calls → Fill call details → Select audio file → Upload
System automatically:
- Transcribes audio to text using Whisper
- Analyzes sentiment and emotions
- Identifies keywords and entities
- Calculates quality metrics
Navigate to Call Analysis → Select call → Review transcription and insights
Supervisors add manual evaluations and feedback
Access Reports section for analytics and export options
Setting Up Keyword Monitoring
🔧 Troubleshooting
Common Issues and Solutions
| Issue | Possible Cause | Solution |
|---|---|---|
| Audio upload fails | File too large or wrong format | Ensure file is under 100MB and in supported format (WAV, MP3, OGG) |
| Poor transcription quality | Audio quality or background noise | Use clear audio recordings, minimize background noise |
| Slow processing | Large file or system load | Use smaller files, check system resources |
| Login issues | Incorrect credentials or account disabled | Verify username/password, contact administrator |
| Missing features | User role restrictions | Contact administrator for role permissions |
System Requirements Check
python3 -c "import whisper; print('Whisper OK')"
# Check NLP libraries
python3 -c "import nltk, textblob, spacy; print('NLP OK')"
# Check audio tools
which ffmpeg
which sox
❓ Frequently Asked Questions
General Questions
Q: What audio formats are supported?
A: The system supports WAV, MP3, and OGG formats. WAV format is recommended for best transcription accuracy.
Q: How long does processing take?
A: Processing time depends on audio length and system load. Typically, 1 minute of audio takes 2-5 minutes to process completely.
Q: Can I process multiple calls at once?
A: Currently, calls are processed one at a time. You can upload multiple calls sequentially.
Technical Questions
Q: What languages are supported for transcription?
A: Whisper supports multiple languages including English, Spanish, French, German, and many others. The system automatically detects the language.
Q: How accurate is the sentiment analysis?
A: Sentiment analysis accuracy is typically 85-90% for clear, well-articulated speech. Accuracy may vary with audio quality and speaking style.
Q: Can I customize the quality scoring criteria?
A: Currently, quality scoring uses predefined algorithms. Contact system administrators for customization options.
Usage Questions
Q: How do I reset my password?
A: Contact your system administrator to reset your password. Administrators can reset passwords through the User Management section.
Q: Can I export data for external analysis?
A: Yes, the system supports exporting reports in PDF, Excel, and CSV formats from the Reports section.
Q: How long is call data stored?
A: Data retention policies are set by system administrators. Typically, call data is stored for 6-12 months based on your organization's policy.