🧪 Testing Methodology
📋 Test Scenarios
We conducted comprehensive testing across multiple scenarios to evaluate Notta's speaker identification performance in real-world conditions.
🎯 Scenario Types:
- 2-person interviews: Clear speaker separation
- 5-person meetings: Multiple voice overlap testing
- 10-person conference: Maximum capacity stress test
- Accented speech: International speaker diversity
- Background noise: Real office environment simulation
🔊 Audio Conditions:
- Studio quality: Professional microphones
- Laptop built-in: Standard video call audio
- Phone recording: Mobile device capture
- Conference room: Shared microphone setup
- Noisy environment: Coffee shop/open office
📊 Accuracy Measurement
Correct Identification
85%
Speakers correctly identified and labeled consistently
False Positives
8%
New speakers created for existing voices
Missed Detection
7%
Voice changes not recognized as new speakers
📈 Performance Analysis
🏆 Strengths
✅ Consistent Performance:
- Stable accuracy: 85% maintained across different sessions
- Good 2-3 speaker handling: 92% accuracy with small groups
- Clear audio optimization: 90%+ with high-quality input
- Fast processing: Real-time results with minimal delay
- Multilingual support: 104 languages with decent accuracy
🎯 Use Case Excellence:
- Client interviews: Perfect for 1:1 or small group calls
- Podcast recording: Reliable host/guest separation
- Training sessions: Instructor/participant distinction
- International calls: Handles accent variations well
- Good value for the feature set
⚠️ Limitations
❌ Technical Constraints:
- 10 speaker limit: Large meetings exceed capacity
- Background noise sensitivity: 65% accuracy in noisy environments
- Similar voice confusion: Family members or similar tones
- Cross-talk issues: Overlapping speech causes errors
- No custom training: Cannot improve with usage data
🔧 Feature Gaps:
- Generic labeling: 'Speaker 1, 2, 3' vs. custom names
- No emotion detection: Missing sentiment analysis
- Limited analytics: Basic talk time metrics only
- No speaker profiles: Cannot remember voices across sessions
- Manual corrections: Time-consuming label editing
🔬 Real-World Test Results
📞 Test Case 1: Client Sales Call (2 Speakers)
Setup
- • 45-minute sales demo
- • Zoom call recording
- • Clear audio quality
- • Minimal background noise
Results
- • 92% accuracy
- • 2 false speaker splits
- • Clean separation
- • 1.5 sec processing delay
Verdict
Excellent
Perfect for sales calls and client interactions
👥 Test Case 2: Team Meeting (6 Speakers)
Setup
- • 30-minute standup
- • Conference room mic
- • Mixed audio quality
- • Some cross-talk
Results
- • 78% accuracy
- • 3 extra speaker labels
- • Some voice merging
- • 3 sec processing delay
Verdict
Good
Workable but requires manual cleanup
🎪 Test Case 3: Large Conference (10 Speakers)
Setup
- • 60-minute all-hands
- • Multiple microphones
- • Variable audio quality
- • Frequent interruptions
Results
- • 62% accuracy
- • Hit 10 speaker limit
- • Significant confusion
- • 5+ sec processing delays
Verdict
Poor
Not suitable for large group meetings
🆚 Competitive Comparison
| Feature | Notta | Otter.ai | Fireflies | Rev.ai |
|---|---|---|---|---|
| Accuracy Rate | 85% | 83% | 88% | 92% |
| Max Speakers | 10 | 10 | 20 | 25 |
| Languages | 104 | English only | 69 | 36 |
| Real-time Processing | 2-5 sec delay | 1-3 sec | 3-7 sec | Near real-time |
| Custom Names | Manual only | AI + Manual | AI + Manual | Full AI |
| Pricing (Pro) | $8.25/month | $10/month | $10/month | $0.025/min |
📊 Competitive Analysis:
🎯 Notta's Advantages:
- • Best multilingual support (104 languages)
- • Competitive pricing at $8.25/month
- • Solid 85% accuracy for most use cases
- • Good performance with clear audio
⚠️ Areas for Improvement:
- • Lower accuracy than Rev.ai and Fireflies
- • Limited to 10 speakers vs competitors
- • Slower real-time processing
- • Basic speaker labeling features
🎯 Use Case Recommendations
✅ Perfect For
- 🗣️ Client calls: 1:1 or small group meetings
- 🎙️ Podcast recording: Host/guest conversations
- 📞 Interviews: Job interviews or research
- 🌍 International calls: Multiple languages needed
- 💰 Budget projects: Good value for money
- 🎓 Training sessions: Clear instructor/student separation
⚠️ Use With Caution
- 👥 Medium meetings: 4-8 people (manual cleanup needed)
- 🔊 Noisy environments: Reduced accuracy expected
- 🎤 Poor audio quality: Built-in mics may struggle
- 💬 Cross-talk heavy: Frequent interruptions
- 👨👩👧👦 Similar voices: Family members or twins
- 📊 Analytics needs: Limited speaker insights
❌ Not Recommended
- 🏢 Large meetings: 10+ participants
- 📞 Conference calls: Multiple dial-ins
- 🎪 Events/webinars: Audience Q&A sessions
- ⚖️ Legal proceedings: High accuracy requirements
- 🏥 Medical dictation: Critical documentation
- 📈 Advanced analytics: Detailed speaker insights needed
🏆 Final Verdict
Overall Score: 7.5/10
Notta offers solid speaker identification performance that excels in small group settings and multilingual environments. While it doesn't lead the market in accuracy, its 85% performance rate and 104-language support make it a compelling choice for international teams on a budget.
8/10
7/10
8/10
7/10
💡 Bottom Line
✅ Choose Notta If:
- • You need multilingual support
- • Budget is a primary concern
- • Most meetings have ≤5 participants
- • Audio quality is generally good
❌ Skip If:
- • You need 95%+ accuracy
- • Large meetings are common
- • Advanced analytics required
- • English-only environment