Speechmatics released a new API including an enhanced transcription engine (2h free per month!) that we integrated into the Auphonic Web Service now.
In this blog post, we also compare the accuracy of all our integrated speech recognition services and present our results.

Automatic speech recognition is most useful to make audio searchable: Even if automatically generated transcripts are not perfect and might be difficult to read (spoken text is very different from written text), they are very valuable if you try to find a specific topic within a one-hour audio file or if you need the exact ...

All the users of Auphonic and Hindenburg – rejoice! We are glad to announce that Hindenburg and Auphonic can now be connected, making your audio editing and post-production process much more straightforward.

Now you do not have to worry any more about manual downloads from Hindenburg and uploads to Auphonic. The new integration allows you to run the production that you edit in Hindenburg through Auphonic algorithms and apply all the audio post-production in just one click: you now can seamlessly transfer the audio file from Hindenburg to Auphonic for further post-production. This step is carried out in ...

Our classic noise reduction algorithms remove broadband background noise and hum in audio files with slowly varying backgrounds.
We released the first beta version of the new dynamic noise reduction algorithms now, which work much better with fast-changing and complex noises. Listen to the audio examples below, they demonstrate some of the new features and use cases!

Glitch While Streaming by Michael Dziedzic.

How to try out the Beta Denoiser

At the moment, only users with access to our advanced algorithm parameters can try the beta noise reduction algorithms (free users: please just ...