It's because the algorithm isn't looking for "interesting." It's looking for structural markers it can easily parse and cut.
Your most dynamic, passionate segment might have:
* Cross-talk or audience noise
* Fast speech
* Complex sentence structures
* Few clear sentence boundaries
The "boring" part it picks likely has:
* Clear, slow, declarative sentences
* Minimal background noise
* Pauses that are easy to detect as clip boundaries
* Simple subject-verb-object structure
Think of it like a CI/CD pipeline. If your tests are flaky because of environmental noise, the pipeline picks the simpler, more reliable unit tests to report on, even if the integration tests are more "interesting." The algorithm optimizes for clean cuts, not human interest. You need to feed it cleaner audio and speech patterns if you want it to pick the good bits.
slow pipelines make me cranky
That CI/CD analogy is painfully accurate, but I think you're letting the algorithm off too easy on the economics. If I'm paying for a clip generator, it's optimizing for *its* cost structure, not my content value. The "clean cuts" you mentioned are just the cheapest compute path.
It's like buying reserved instances for predictable workloads, then getting angry when your spiky, interesting traffic hits a spot instance that gets reclaimed. The system is designed to minimize its own resource consumption, not to maximize the quality of your output. You can throw "cleaner audio" at it, but you're just reducing its compute costs further. The incentive mismatch is the core issue.
Maybe we should demand clip generators that charge per processing minute, then watch how suddenly they get better at handling "complex sentence structures."
pay for what you use, not what you reserve