DeepL and Whisper Quietly Save Time
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In short
Whisper runs locally, so transcription can be built into your own application without sending any audio to the cloud.
DeepL — making English read naturally
We use it for reports and replying to email.
The best part is simply that the English reads naturally. There is little of the stiffness that gives machine translation away, and the output is usable as-is.
What actually helped was less the translation quality than the change in order. Even when writing English feels like a chore, switching to “draft in Japanese, then polish” lowers the barrier.
Whisper — transcription that runs locally
We used it when building an app that handles speech recognition.
We picked it because it runs locally and is accurate. Everything stays on the machine, so no audio goes to the cloud. That is strong both for privacy and for offline operation.
It became the first candidate whenever the requirement is “build transcription into my own app”.
Choosing between them
| Task | Tool |
|---|---|
| Writing and polishing English | DeepL |
| Turning speech into text, embedded in an app | Whisper (local) |
“Where it runs” as a selection criterion
Putting the two side by side shows that accuracy is not the only axis in a selection.
Accuracy was part of why we chose Whisper, but what really mattered was where it runs. “Audio never goes to the cloud” is not something you can add later the way accuracy can be improved. It is an architectural constraint, and it has to be decided first.
Rather than spending time comparing headline features, deciding “where does it run” and “what leaves the machine” first narrows the options on its own.
Frequently asked questions
Q1Writing English is slow. What should I change first?
Stop starting in English. Draft in Japanese and then polish through translation. Finishing a translated draft is faster than assembling English from nothing, and the result reads more naturally.
Q2What are the options for building transcription into an app?
Requiring it to run locally narrows the field quickly. Keeping it on the machine means audio never leaves, and it works offline. If the audio touches privacy at all, make that a requirement from the start.
Q3Are these free to use?
Whisper is free to run. DeepL's free tier is enough for everyday use. Both have a low barrier to getting started.
What this article is based on
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