The technical challenge
Dolphin is specially optimized to handle 22 Chinese dialects, which are often misrecognized by common speech recognition models due to their pronunciation variability and regional characteristics.
Specific steps
- Double Marker Positioning: Precise designation of dialect area codes
dolphin dialect.wav --lang_sym "zh" --region_sym "TW" # 台湾闽南语
- Model Selection Recommendations::
- Base scenario: using the BASE model (fast response)
- Specialized scenarios: small model selected (error rate reduced by 8.11 TP3T)
- data enhancement::
- pass (a bill or inspection etc)
--padding_speech truefiller phrase - Incorporation of ambient noise during pre-processing (signal-to-noise ratio controlled at around 20 dB)
- pass (a bill or inspection etc)
Tuning program
Developers can be based on open source code:
1. Indolphin/models/Add a customized dialect dataset to the directory
2. Modificationsconfigs/regional_config.yamlEnhancing dialect-specific feature weights
3. Utilizationpython train.py --dialect_mode=truefine tune
This answer comes from the articleDolphin: Asian Language Recognition and Speech-to-Text Modeling for Asian LanguagesThe
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