yeyupiaoling/Whisper-Finetune
Fine-tune the Whisper speech recognition model to support training without timestamp data, training with timestamp data, and training without speech data. Accelerate inference and support Web deployment, Windows desktop deployment, and Android deployment
This project helps you improve the accuracy and speed of transcribing audio into text using the Whisper speech recognition system. It allows you to customize the system with your own audio recordings and their corresponding text, even if your data doesn't include exact timing information. The enhanced system can then quickly convert new audio files into accurate written transcripts, and can be deployed in web applications, desktop programs, or Android devices. This is for professionals like journalists, researchers, or content creators who need highly accurate and fast audio transcription tailored to specific languages or accents.
1,200 stars.
Use this if you need to fine-tune the Whisper speech recognition model for a specific language, accent, or domain, and want to improve transcription accuracy and inference speed for deployment across various platforms.
Not ideal if you just need basic, off-the-shelf audio transcription without any customization or specialized deployment needs.
Stars
1,200
Forks
213
Language
C
License
Apache-2.0
Category
Last pushed
Dec 17, 2025
Commits (30d)
0
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