Methods of constructing a pronunciation training system
The application of Seed-VC to language teaching needs to be implemented in three stages:
- Basic Comparison System::
1. Recording of standardized pronunciation by native speakers as reference audio (recommended to include the full set of phonemes)
2. Students record and then perform the conversion:python inference.py --source student.wav --target native.wav --output compare.wav
3. Comparative analysis of sound spectra using Praat software - Real-time feedback program::
1. Configure the real-time processing pipeline:
- Microphone → Seed-VC (real-time mode) → headphone monitoring
- Set 300ms delay buffer to ensure integrity
2. Development of intensive training modules:
- Highlighting difference syllables (Python+librosa)
- Generate articulatory heat maps (using the GPT-4 speech evaluation API) - Course System Design::
1. Phased construction of sound libraries by CEFR level (A1-C2)
2. Design of specialized training:
- Conversion of the serialized weak form
- Reproduction of tone contours
- Stress pattern matching
3. Integrate Anki to create smart memory cards
Note: It is recommended to keep the original pitch (f0-condition=False) in order to expose articulation problems.
This answer comes from the articleSeed-VC: supports real-time conversion of speech and song with fewer samplesThe
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