Podcast to Podcast: Content Localization Using OpenAI API Stack
summary
Pipeline converts English podcasts to Russian end-to-end using Whisper-1 transcription, GPT-4o for punctuation, grammar and translation, and TTS-1 voice synthesis with 4,000‑char chunks. System written in Kotlin, pulls feeds from podcastindex.org via podcast4j, outputs RSS and merges audio (FFMPEG planned) while handling Whisper’s 25 MB file limit and MP3 metadata conflicts. Claims automated localization preserves tone and style but notes a slight American accent in synthesized Russian and relies on manual QA plus planned BLEU scoring.
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chapters (10)
- 0:00Introduction to Podcast Localization
- 0:15Why Automate Podcast Localization?
- 0:53System Architecture Overview
- 3:02Key Technologies and Tools
- 5:13Detailed Pipeline Steps
- 8:38Challenges and Solutions
- 13:35Quality Assurance Measures
- 14:25Code Snippets and Examples
- 18:47Future Improvements
- 19:20Conclusion and Key Takeaways
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