Whisper App's transcription system utilizes a multi-tier technology architecture with the following distinguishing features:
- model combination::
- The front-end uses Together.ai's Whisper model to implement speech-to-text base conversion, supporting up to 5 minutes of continuous recording
- Back-end integration with Llama model for text post-processing, including grammar correction and formatting optimization
- multilingual engine: Multi-language capability based on Whisper model to handle mixed input in common languages such as Chinese, English, Spanish, etc.
- on-line processingSynchronization and version control during transcription through real-time database services provided by Convex.
- Precision control: Recommended for use in quiet environments, the system automatically recognizes and filters non-voice noise (e.g., keyboard tapping)
In terms of technical limitations, the current version relies on the parameter configuration of Together.ai for terminology recognition, and the dialect recognition accuracy is about 75%. future versions are planned to add a local model caching mechanism to reduce the network dependency.
This answer comes from the articleWhisper App: free speech-to-text & AI note organizer toolThe
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