Background to the issue
Audibit's dual technology solution ensures accurate pronunciation of technology articles, which often contain programming terms (e.g. Kubernetes), mathematical symbols, and other special content that can be easily misinterpreted by conventional TTS engines.
Technology solution paths
- pretreatment stage::
- Add term substitution rules before OpenAI API calls (edit src/utils/textProcessor.js)
- Enable
tag isolation for code snippets
- Engine Selection::
- Technical content prioritizes the use of Lemonfox's Academic Speech Library.
- Common content using OpenAI's whisper-large model
Maintenance program
Create a customized thesaurus (stored in public/glossary.json) that can be supplemented with new terms by community users via Pull Request. Suggestions for specialized terms that appear consistently:
- Adding phonetic annotations to the pronunciation field in the Firestore database
- Identifying Similar Terms for Unified Processing via Pinecone Vector Search
When an immediate problem is encountered, it can be temporarily solved by using the phonetic annotation method (e.g. @pragma → [praegma]).
This answer comes from the articleAudibit: turning popular tech articles into ready-to-listen audio podcastsThe
May not be reproduced without permission:AI productivity tools " How to solve the problem of pronouncing technical terms in technical articles after text to audio conversion?
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