The transcription and summarization effects of Recap depend on the following factors:
- Transcription quality: Based on WhisperKit technology, accuracy is high but is affected by audio clarity (e.g. background noise) and device performance. Recommended for use in quiet environments and to ensure that the device has sufficient storage space.
- Abstract Generation: The default Ollama local summarization is suitable for extracting simple key points (e.g., meeting decisions), while OpenRouter provides higher quality contextual summarization, but requires networking and relies on API configuration.
- user intervention: The transcribed text supports manual editing, which allows users to correct recognition errors before generating summaries, improving the quality of the final output.
The developers have indicated that they will continue to optimize the model selection and integration approach in the future.
This answer comes from the articleRecap: macOS Local Meeting Audio Transcription and Summarization ToolThe
May not be reproduced without permission:AI productivity tools " How effective are the transcription and summarization functions of Recap? What are the influencing factors?
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