Five key techniques for naturalized speech generation
For the AI dubbing mechanical sense problem, Xunfei Intelligent Work provides professional-grade solutions:
| Type of problem | cure | Parameter recommendations |
|---|---|---|
| lack of synchronization | Using the "Rhyme Marker" function - Stress marks added to key vocabulary - Interrogative endings are set up in an upward manner |
Tone fluctuation values suggested 60-80% |
| lack of a sense of breath | - Insertion of 0.2 seconds of air gaps every 120 words - Enable "natural breathing sounds" option |
Breath volume to 151 TP3T. |
| emotionally deficient | - Selection of "Emotionally Intensive" Anchor Type - Insert expression labels such as [Smile][Serious] in text |
Emotional Intensity Recommendation 40% |
Higher-order programs:
1. Segmentation of the text according to mood and cross-dubbing using different anchor voices
2. Add background ambient sound (e.g. café white noise) for 5%-10%
3. Micro-noise reduction after output using software such as AU (retaining the 200-5000 Hz band)
This answer comes from the articleCyberSmart: Converting Text to Speech and Digital Human VideoThe
May not be reproduced without permission:AI productivity tools " How to overcome the mechanical problems that occur when dubbing long texts?
