Why do pronunciation metrics fail for expressive TTS?

In expressive Text-to-Speech (TTS) systems, pronunciation accuracy is necessary but not sufficient.

Phoneme precision ensures words are spoken correctly. It does not ensure the speech feels alive, emotionally aligned, or contextually appropriate. Expressive TTS is evaluated not only by what is said, but how it is delivered.

Structural Limitations of Pronunciation Metrics

Pronunciation metrics isolate phoneme accuracy, articulation clarity, and stress placement. These are measurable and important.

However, expressive quality depends on rhythm variation, tonal contour, pacing shifts, and emotional inflection. A system can score highly on pronunciation while sounding flat, mechanical, or disengaging.

Technical correctness does not equal perceptual authenticity.

Context Defines Expressive Success

Expressiveness is use-case dependent.

• Storytelling requires warmth, modulation, and dynamic pacing.

• Financial reporting demands stability, clarity, and authority.

• Customer support benefits from approachability and responsiveness.

If evaluation focuses only on phonetic correctness, these contextual requirements remain invisible. The model may pass validation while failing user expectations.

Risks of Over-Prioritizing Phoneme Accuracy

1. Emotional Flatness Approval: Models may be approved despite lacking expressive variation.

2. User Disengagement: Technically accurate but monotonous output reduces satisfaction and trust.

3. Hidden Performance Drift: Prosodic instability may develop without affecting pronunciation scores.

4. Misguided Optimization: Teams may refine articulation while neglecting tonal dynamics.

Holistic Evaluation Approaches

• Attribute-Level Assessment: Evaluate naturalness, expressiveness, emotional appropriateness, rhythm stability, and contextual tone alignment independently.

• Paired Comparisons: Use direct A versus B comparisons to surface perceptual differences in expressive delivery.

• Human-Centered Evaluation: Engage native speakers and domain-aligned listeners to capture emotional nuance and contextual authenticity.

• Scenario-Based Testing: Validate expressive performance within realistic prompts rather than isolated sentences.

Practical Takeaway

Pronunciation metrics measure accuracy. Expressive evaluation measures impact.

Effective TTS evaluation frameworks treat phonetic precision as a baseline requirement while prioritizing perceptual engagement and contextual alignment.

At FutureBeeAI, structured evaluation methodologies integrate pronunciation diagnostics with expressive attribute analysis to ensure TTS systems are not only correct, but compelling and contextually credible.