Haven't have a chance to test AWS Transcribe yet but I run a benchmark of IBM, Microsoft and Google transcription api weekly.

So far, IBM watson work best for english, google in other . language. For example the transcript of trump inauguration speech (16minutes 38seconds, 8371 character) give me a levenshtein distance to the official one of (smaller is better) :

- IBM : 898 (566130ms)

- Google : 1249 (301635ms)

- Microsoft : 5233 (109391ms)

This is not a far comparison. IBM is the leader because they have a product that is specifically designed for this whereas the others do not.

Do you have some github or link as this is interesting to follow the quality of these transcription services

I tried to use this, but it looks like they have to review me for access.

I've tried the IBM and Google transcription APIs on a podcast with overlapping speakers, and they turned out dadaist poetry. I've been meaning to check out other solutions.

* Google: http://mefiwiki.com/wiki/Podcast_107_Transcript_(automated)

* IBM Watson: http://mefiwiki.com/wiki/Podcast_117_Transcript_(automated)

Where's the audio? We also provide automated transcripts and I'd love to compare it.

Click the "Episode ___" link in the first paragraph, then search for "Direct mp3 download" on that page.

I'd love to see more details on what you do. I haven't found a good automated solution yet. It seems like the solutions with acceptable quality involve Mechanical Turk.

Edit: I added a Bing attempt, and I'll link the list, rather than individual eps: http://mefiwiki.com/wiki/Podcast#automated_transcripts

Here's the automated transcript from our system. I checked around a minute or so and looks like accuracy is around 80%.

https://scribie.com/transcript/c5ae0522950c421c9d939dc8a17f4...

Hmm. Is it $0.60/min for the automated solution?

Automated transcripts are free. That's the pricing for our manual transcription.

https://scribie.com/transcription/free

I've tested the google API and I'd say it's quality is similar to what I see in this example result. In other words, not great.

For me, this isn't close enough to be considered a "valid" transcription. Too much information is lost. Too much context is lost.

Truly looking forward to a day when ML / AI can do this with high degrees of accuracy, but we're not there yet.