Background requirements
For e-books, course handouts and other 10,000-word content, conventional tools have problems such as processing interruptions and misaligned segments.
systematized program
- Technology realization path
- Split documents into multiple .txt files by chapter (≤5000 characters per file)
- Batch submission via project API interface (concurrency ≤ 3 to be configured)
- Receive processing completion notifications using a webhook
- automated configuration
- Set MAX_BATCH_SIZE=2000 in .env
- Timed execution of scripts/auto_convert.py via crontab
- Output files are automatically named and stored by UUID
- Exception handling
- Supports intermittent transfer after network interruption
- Providing log/error_details.json error logs
- Programmable character quota warning thresholds
Efficiency Improvement Tips
For duplicate content it is recommended to enable the speech caching feature, where the same text hash is synthesized only once.
This answer comes from the articleOpen source operational project integrating multiple advanced speech synthesis servicesThe
May not be reproduced without permission:AI productivity tools " How to automate speech synthesis for large-scale text?
