Convert MP3 to text

This is the question people ask before re-exporting a file at higher quality, so in August 2026 we measured it against our own live pipeline. We took one spoken recording and encoded it as MP3 four times, at 320, 128, 64 and 32 kbps, then sent all four through the identical transcription request.

All four came back with byte-identical transcripts. Not similar: the same text, word for word, punctuation included. The 32 kbps file was 108 KB against 1,083 KB for the 320 kbps version, so it carried a tenth of the data and produced exactly the same result. A 32 kbps MP3 sounds noticeably worse to a human ear, and the speech model did not care.

The practical consequence is that re-exporting an MP3 at a higher bitrate before uploading is wasted effort, and choosing a smaller export is a free speed win: less to upload, nothing lost. What genuinely moves accuracy is the recording itself, meaning microphone distance, background noise and how clearly people speak, none of which a bitrate change can repair after the fact.

One detail from the same test makes the point better than the bitrates do. The recording contained the name Anneliese, and every single version transcribed it as Annalise. Identical error at 320 kbps and at 32 kbps, because the difficulty was in the name rather than in the file. The Polish surname Kowalczyk, meanwhile, came back correct at every bitrate.

MP3 is the default export from most recorders, podcast platforms and download tools, which is why it arrives more often than any other format. That variety is also why the audio underneath ranges from a studio microphone to a phone in a coat pocket, and the transcript quality follows the recording, not the extension.

Whatever the source, spend the first two minutes on names and numbers rather than reading the whole transcript. Names are where speech recognition slips, as our test showed, and you can prevent most of it by typing recurring names and jargon into the vocabulary box before uploading, which is available on every plan including free. Spoken figures are converted to digits automatically, so three point two million arrives as 3,200,000 and eleven percent as 11%, which is usually what you want in a working document but deserves a glance when a currency amount has to be exact.