Otter.ai
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Transcription that finally gets English & non-English languages right
Which is more popular?
Website, pricing, platforms and company facts side by side.
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Transcriber
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| Website | transcribe.zpoken.ai | transcriptgo.app |
| Pricing | — | |
| Platforms | — | |
| Listed in |
What each product offers, as listed by its team.

Possible disadvantages
How often each product is chosen within a category, 0–100% relative to the other.

As answered by people managing Transcriber and TranscriptGo.app.
TranscriptGo.app's answer:
Most transcription tools are built for English and treat every other language as an afterthought. TranscriptGo sends each language to the speech engine that handles it best. Bangla, Hindi, Urdu and Arabic each get their own engine plus a spelling pass. The difference shows up quickly. Many tools quietly stop partway through a long Bangla or Hindi recording, and we transcribe it all the way to the end, with correct spelling. You also get timestamps, subtitles, translation and a summary from one upload.
TranscriptGo.app's answer:
There are three reasons:
You can try it on your own recordings with the free monthly minutes before you pay anything.
TranscriptGo.app's answer:
It's for people who work with spoken content, especially outside English:
A large share of our users speak Bangla, Hindi or Urdu, because that's where other tools let them down.
TranscriptGo.app's answer:
I needed Bangla recordings turned into text and tried every popular transcription tool. The results were half-finished transcripts, broken spelling, and prices charged per minute. The tools were clearly built for English first. So I built one for myself: a separate engine for each language, a check that the whole recording actually gets transcribed, and pricing that doesn't punish you for long files. It grew from there into 99+ languages, and it's still built around one rule: the transcript has to be complete and correct.
TranscriptGo.app's answer:
The backend runs on Laravel (PHP), and the frontend is Vue with Inertia. Videos are prepared in the browser with FFmpeg (WebAssembly), which extracts a small audio track so uploads stay quick. Files are kept in S3-compatible object storage. Transcription, translation and summaries run on a mix of leading speech and language AI models, and the engine is chosen separately for each language.
Share your experience with using Transcriber and TranscriptGo.app. For example, how are they different and which one is better?
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