r/nodered • u/AizlynMaeve • 25d ago

Best speech-to-text API for developers adding transcription to an app?

I'm building a web app and I want to add a feature where users can upload audio files and get a transcript back.

I don't want to build or manage the infrastructure myself. 

What is the best speech-to-text API that is easy to implement, handles long files, and returns timestamps and speaker labels?

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u/SignalMap2750 25d ago

You can try the API for dadascribe.com, a system I created a while ago for my own use to transcribe instructional videos and interviews for another website of mine, and then I scaled it for others to use.  It is based on Whisper and has a custom pipeline that improves accuracy to 99.5%. It handles noisy setups and multiple speakers, lyrics, you name it. And yes, it returns timestamps and speaker labels for diarization, as well as up to 10 hours audio files. You can review the API info at api.dadascribe.com and I hope it works for you.

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u/AizlynMaeve 19d ago

Thank you I will look at it.

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u/SignalMap2750 19d ago

Sure! Eager to know your thoughts about it.

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u/[deleted] 16h ago

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u/SignalMap2750 15h ago

I created it, and it works well. You can start here: http://api.dadascribe.com/

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u/Suspectaque 19d ago

If I may self-plug, I made https://opentranscription.io exactly for this. Rather than committing to one provider, most of the major ones sit behind a single REST endpoint and one key, and the response comes back in the same shape whichever model runs it, so switching later is one field rather than a rewrite. Speaker labels and word timestamps depend on the model you pick, and there's a leaderboard with WER per model measured on the same audio if you want to compare accuracy before committing.

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u/newsdisttext 8m ago edited 3m ago

For long recordings, I’d put more weight on speaker diarization and timestamps than the headline transcription accuracy. That’s where the annoying cleanup starts.

I tested Speechmatics for a project and the output was pretty good, especially the speaker separation and word-level timestamps.

It also has batch transcription, so you don’t have to build a separate workflow just to handle longer files. I’d run a few of your actual recordings through it before committing, especially if the audio has multiple speakers.