Cleanvoice Transcripts

Cleanvoice Transcripts is the right pick when you want one tool to clean and transcribe in one pass, with everything timestamp-aligned. The flagship Cleanvoice product removes filler words ('um', 'uh', mouth clicks, long pauses) from podcast episodes, and the transcripts feature was added to complement that workflow.

The differentiator is alignment: transcripts come back with timestamps that map to the cleaned audio output, not the raw input. If you've ever tried to align a transcript with an edited version of the same audio, you know how much friction that integration removes.

The filler-word stats baked into the report add a useful editorial dimension. You can see exactly how many times a host or guest said 'like' or 'you know', which can be eye-opening data for hosts working on speech habits or producers managing show quality across episodes.

An API is available for teams building automated workflows. The trade-offs are honest. If you don't already use Cleanvoice for filler removal, you're paying for a bundled feature you don't need; pure-transcription pricing elsewhere is lower.

There's no human review tier, so accuracy floor is set by the underlying ASR model. Cleanvoice's main product is what you're really buying, and transcripts are the cherry on top.

For podcasters already paying Cleanvoice for cleanup, the transcript add-on is genuinely useful. For others, the Whisper API or Deepgram is more cost-effective.