Original Summary

I run a tiny SaaS that turns movies into 60-sec recap Shorts. 279 free users, $0 MRR, so no victory lap here, just an honest war story. Our narrator sounded cheap in three ways. It randomly laughed mid-sentence on emotional words (yes, at funerals). It rushed like a chipmunk. And the opening line was always quieter than the rest. Nobody complains about this stuff, people just leave, so it took us a while to even notice how bad it was. The laughter was the weirdest one. The voice model just ad-libs laughter around dramatic words. Turning down its randomness setting step by step killed almost all of it. We also strip stage directions like [laughs] from scripts now, because it used to perform them literally. Then the chipmunk thing. Logs showed the audio was getting sped up twice, once during generation and once in editing. 1.2 x 1.1 doesn't sound like much, but stacked it sounds rushed and robotic. Now tempo gets applied exactly once, with an automated check so it can't silently come back (it already did once, fun times). And the quiet hook. Every line is voiced separately with different energy, and our volume normalizer adapted on the fly, so each line landed at a different loudness. Now we measure each line first and level them all to the same target. What I took away from this: measure, don't guess. The double speed-up was invisible until I divided real audio durations by line count. Also, bad audio is a silent killer, nobody reports it, they churn. And lock your fixes with automated checks. Happy to answer anything about the pipeline. Roast my approach? https://reddit.com/link/1x52rwg/video/5bdkfouaq9vh1/player   submitted by   /u/aivideorecap [link]   [comments]

  • 情报分类：开源项目与落地
  • 分类依据：内容涉及项目实践、创业、副业或变现
  • 信息来源：Reddit · SaaS
  • 发布时间：2026/10/14 01:21:40