
Drop an MP3 or WAV file, add a video podcast in MP4 or MOV, or paste a link. Audio files up to five hours go through in a single upload, and both audio or video formats are handled the same way. Whichever file you start from, the podcast transcription runs the same: one upload, one click, one transcript. For a short clip it is finished before you are done exporting the audio file.

Pick the spoken language - or let the AI handle it, since it detects the original language and the number of speakers on its own. The podcast transcript generator writes out every word, timestamps each segment, and separates the voices from the background mix as it goes. You can transcribe in the original language, or transcribe and translate the episode in a single pass - the podcast transcription and the translation come out of the same run.

Read the transcript next to the player, fix a name or a term, and download the finished transcript. Rask AI writes the podcast transcript as an .srt file, which is plain text underneath - copying it into a Word document, a PDF, or your show notes template is one paste away. Download the transcript as often as you like: the file stays in your account, so you can edit it and download it again tomorrow.
Room echo, a guest on a laptop mic, the occasional bit of overlapping speech - that is what podcast audio actually sounds like, and Rask AI separates each voice from the background mix before the transcription starts. Audio quality is still what decides the outcome: a separate microphone per guest and a quiet room give you high accuracy on the first pass, and anything messier leaves you two or three lines to touch up. Either way you end up with accurate transcripts you can publish, not a draft you have to rebuild. Rask AI will transcribe a podcast episode of any length at the same quality - a two-minute trailer and a two-hour interview go through exactly the same model, and a highly accurate transcript costs you the same either way.
An interview transcript is useless if you cannot tell who said what. Rask AI detects multiple speakers automatically and applies speaker labels to each segment, and you can rename them to real names in the editor in a couple of clicks. Speaker identification is what makes interview episodes readable and keeps every quote attributable to the right guest, which matters the moment you publish podcast transcripts publicly. Timestamps sit on each line as well, so the transcript doubles as a map of the episode: click a phrase and you jump directly to that point in the audio.
A single transcript is the cheapest content engine a podcast has, and podcast transcripts are the one asset that keeps working after the release. Pull the key topics, the key points, and the best quotes, and the same podcast episode becomes show notes, two blog posts, a newsletter, and a run of social clips - content creation stops starting from a blank page. Podcast transcripts also give search engines something to index, so an episode keeps earning attention long after the week it went live. One podcast transcript feeds the newsletter, the captions on your clips, and the summaries your team writes for the show page - repurpose episodes across multiple platforms and a single transcript covers a week of publishing.

If you publish on your own, the manual work is what kills the schedule. A podcast transcript generator removes the slowest part of it and hands you podcast transcripts while you are still making coffee: you upload the episode, get the text back in minutes, and spend your time on the edit rather than on typing. It is the cheapest hire a solo show can make - no scheduling, no per-minute invoice, and you transcribe your own episodes the day they drop. From one file you get an episode transcript for the show page, a full transcript for your archive, searchable text you can grep, and the phrases you need for social media posts. The free plan is there to test the first episode before you commit. Reading is faster than listening, so some people will scan the complete transcript instead of listening, while others read while listening because it helps them follow a technical episode. Offering both is what grows a show. Publish the transcript on the episode page first - that is where search picks it up - then reuse it in the notes on Apple Podcasts, in your newsletter, and under the video. Apple Podcasts, Spotify, and your own site all take the same text. Free podcast transcription covers the first minute of a file, so try it on the episode you are least happy with the audio on.

The more voices in the room, the more a transcript is worth. Rask AI separates different speakers, so a panel of four reads like a script instead of a wall of text, and you can jump directly to specific moments in the recording by clicking a line. For shows with international guests, the podcast transcription can be translated into multiple languages, which lets you publish the same episode for an audience that does not share the spoken language of the original - and Rask AI can dub that episode with a cloned voice on top of the translation. Everything stays in one place: the podcast audio, the transcript, and the translated versions of it, ready to download in multiple formats when you need them, in every language you transcribe into. Your listening figures stay where they are while readers get a text version of the same episode.

For a network, transcripts are infrastructure. Every episode arrives with accurate transcripts attached, podcast transcripts turn the archive into searchable text in every one of your formats, and a producer can find a quote from eight months ago in seconds instead of scrubbing through the audio. Teams share a workspace and a pool of minutes, so a single account covers several shows, and on the Business plan the API plugs the podcast transcription step into whatever publishing pipeline you already run. Podcast transcription at scale means you transcribe every new episode on the day it drops, so the podcast transcripts land with the release instead of a month after it. Transcribe the back catalogue in the same workspace and the archive stops being a pile of audio files. Accessibility is the other half: when you provide transcripts you open the catalogue to deaf and hard-of-hearing listeners, and easy sharing download links mean a sponsor or a PR team can grab the text without asking you for it.
There is a free tier, but be clear on what it covers: seven days, three files, and the first minute of each. That is enough free podcast transcription of a real file to hear how the AI handles your mics and your guests - not enough for a full podcast episode. After that, plans start at 25 minutes a month. Free transcripts of a whole show are not on the table, and we would rather say so than let you find out after the upload.
MP3 and WAV for podcast audio, MP4, MOV, WEBM and MKV for a video podcast - multiple formats in, one transcription out. Both audio files and video files run through the same pipeline, so a screen recording of your episode works as well as the raw audio, and the podcast transcription is identical either way.
It comes down to audio quality. Two guests on one microphone, heavy background noise, or a lot of overlapping speech will need a short pass in the editor; clean, close-mic speech comes back close to perfect. Rask AI separates each voice from the background mix first, which is why a noisy room hurts less than it does with most AI transcription tools, and why high accuracy is realistic on a normal home setup.
Yes. Speaker identification runs automatically during the transcription, and each segment gets speaker labels you can rename. For interview episodes that is the difference between a usable transcript and a wall of text.
Every segment is editable next to the player. Fix a name, correct a term, delete a false start, or merge two lines - the timings stay where they are, so you can edit as much as you like without breaking the sync. Nothing is locked after export: reopen the transcription and download a corrected version whenever you want. The AI also offers alternative wordings per segment when you are working in a second language.
Five formats come out of one project: the video, the video with subtitles, the audio, the video with lip-sync, and the transcript as an .srt file. The .srt is plain text, so the formats downstream - a doc, a PDF, a CMS field - are a copy away.
It gives search engines the one thing an audio file does not have: text. An AI powered transcription makes the episode searchable, and podcast transcripts let Google index the words you actually said, which is how a listener finds an old podcast episode through a search for a topic you covered in passing.
Once you've created the subtitled video, you can upload it video directly to various social media channels. The tool is designed to make sharing easy, so you can reach your audience on platforms like Facebook, Instagram, YouTube, and more.Rask AI can translate podcast transcripts into 135+ languages and dub the podcast with a cloned voice on top of that. For a show with international guests, one recording covers several markets and several podcast platforms at once.
Up to five hours per file. Longer shows are processed in the background, so you can upload, close the tab, and come back when the podcast transcription is done. Queue a batch of files and each one is transcribed separately.
That is what most people do with it. Rask AI gives you the podcast transcript; the show notes and summaries you write from it - that split is deliberate, and a summary is only as good as the transcription underneath it. Having every word of the episode in front of you turns a two-hour re-listen into a five-minute pass, and the chapter markers fall out of the timestamps. Most hosts draft their summaries straight from the transcription rather than from memory.
Team workspaces let you invite an editor or a producer and share subscription minutes, and you can share a project link instead of mailing files. Handy when one person records the podcast and another one turns the transcript into social media content.
Most other tools stop at the text. Rask AI will transcribe the podcast episode, translate it, generate captions for the video version, and dub it in another voice - one place to transcribe, one place to publish from - the transcript is the starting point rather than the finished product, which is what makes it a game changer for a show that wants to grow beyond one language.