AI transcription vs human transcription
Human transcription services (Rev, Scribie, GoTranscript) charge $1-2 per audio minute and take hours to days. Human accuracy is ~99%. AI transcription is dramatically cheaper, returns in minutes, hits 92-97% accuracy on clean audio. For working transcripts, content repurposing, research coding, and most professional use cases, AI accuracy is sufficient with a verification pass against the audio for any verbatim quote. For high-stakes verbatim records (court transcripts, regulatory testimony), human transcription remains the right choice.
What "transcribe audio" does here
Upload an audio file (MP3, WAV, M4A, FLAC, OGG, AAC, WebM, AMR), click convert, download a text file with the transcribed words. Auto-detects language across 50+ supported languages. Auto-handles punctuation and paragraph breaks. Plain UTF-8 output, copy-paste-ready, no formatting markup. For structured Markdown output with speakers and timestamps, switch to the Markdown variant.
For batch back-catalogue work, go OSS
If you have 100+ files to transcribe in one go (back-catalogue podcast, archive of interviews, library of recorded lectures), use faster-whisper locally on a GPU box. Same model class, MIT-licensed, processes hundreds of hours overnight, free. mdisbetter's web tool is for one-at-a-time conversions where the per-file workflow is acceptable.