IndexTTS2 Performance
Superior Benchmarks & State-of-the-Art Model Comparisons
Revolutionary Performance Metrics
IndexTTS2 consistently outperforms state-of-the-art zero-shot TTS models across multiple evaluation metrics, establishing new benchmarks in the field. Our comprehensive testing methodology ensures reliable and reproducible results.
Key Performance Metrics
Word Error Rate (WER)
Significantly lower than competing models, ensuring exceptional speech intelligibility and accuracy in text-to-speech conversion.
Speaker Similarity
Outstanding voice cloning accuracy, surpassing all competing models in speaker identity preservation and voice quality.
Emotional Fidelity
Superior emotion reproduction and control capabilities in zero-shot scenarios, enabling natural emotional expression.
High subjective quality ratings across prosody, timbre, and sound quality, validated through extensive human evaluation.
Performance Visualization
WER Comparison
Word Error Rate comparison across different TTS models, showing IndexTTS2's superior accuracy.
Speaker Similarity
Speaker similarity scores demonstrating IndexTTS2's exceptional voice cloning capabilities.
Emotional Fidelity
Emotional fidelity comparison showing IndexTTS2's advanced emotion control features.
Overall Performance
Comprehensive performance overview across all key metrics, highlighting IndexTTS2's superiority.
Model Comparisons
IndexTTS2 has been extensively compared against leading zero-shot TTS models including MaskGCT, F5-TTS, and XTTS. Our comprehensive evaluation demonstrates consistent superiority across all performance metrics.
Model | WER (%) | Speaker Similarity | Emotional Fidelity | MOS | Processing Speed |
---|---|---|---|---|---|
IndexTTS2 | 1.2 | 4.5/5.0 | 4.3/5.0 | 4.01/5.0 | 1.0x |
MaskGCT | 2.1 | 4.1/5.0 | 3.9/5.0 | 3.75/5.0 | 1.2x |
F5-TTS | 2.8 | 3.8/5.0 | 3.5/5.0 | 3.52/5.0 | 1.5x |
XTTS | 2.5 | 4.0/5.0 | 3.7/5.0 | 3.68/5.0 | 1.3x |
Testing Methodology
Evaluation Dataset
Comprehensive testing on diverse datasets including LibriTTS, VCTK, and custom evaluation sets covering multiple languages, speakers, and emotional expressions.
- Multi-language evaluation
- Diverse speaker demographics
- Emotional expression testing
- Real-world scenario validation
Objective Metrics
Rigorous evaluation using industry-standard metrics including Word Error Rate, Speaker Similarity, and automated quality assessment.
- WER calculation methodology
- Speaker similarity scoring
- Automated quality metrics
- Statistical significance testing
Subjective Evaluation
Human evaluation by trained listeners using Mean Opinion Score methodology for comprehensive quality assessment.
- Expert listener panels
- Blind evaluation protocols
- Statistical analysis
- Inter-rater reliability