AI BriefingHow Inflearn Automatically Generates Subtitles (AI/Infrastructure Edition)
Key point
This covers the process by which Inflearn built its infrastructure using the Whisper model for cost-efficient AI subtitle generation.
Details
Inflearn adopted the lecture AI subtitle feature as an idea through an in-house hackathon, and began the technical journey to implement it as an official service. As core requirements for subtitle generation, they set offline operation, minimizing additional costs, and fast processing speed.
After review, they chose OpenAI's Whisper model to avoid issues with external data transfer and costs. To improve implementation efficiency, they built a pipeline that extracts audio from video and generates srt subtitles using whisper.cpp, the C++ port, instead of the Python version.
To turn this into a service, they tried to leverage the existing AWS Batch-based video encoding infrastructure, but encountered a performance issue where processing a 28-minute video took 69 minutes on a CPU-based instance (c6i.xlarge). To solve this, they conducted a PoC using GPU instances (g5) to explore the optimal infrastructure configuration.
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