how to transcribe a podcast
Most podcast transcription guides give you 10 steps when you need 3. Here are the actual questions podcasters ask, answered directly. Upload your episode, get a transcript with speaker labels, and move on.
what file formats work?
SHRP accepts MP3, WAV, M4A, MP4, MOV, OGG, FLAC, and WebM. MP3 is the most common podcast export format and works perfectly fine for transcription. If your host (Riverside, Zencastr, Descript) exports WAV or FLAC, those give slightly better accuracy since they are lossless formats. M4A files from iPhone recordings and Voice Memos are also fully supported. If you have a video podcast in MP4 or MOV format, SHRP extracts and transcribes the audio track automatically. Most podcast files are well under the 500MB upload limit on Pro.
what about multiple speakers?
Speaker diarization is enabled automatically. SHRP detects distinct voices in your audio and labels them as Speaker A, Speaker B, Speaker C, and so on throughout the transcript. This works well for standard podcast formats: host-guest interviews, co-hosted shows, and panel discussions. The speaker labels carry through to every export format, including SRT subtitles and DOCX documents. For best results, make sure each speaker has a reasonably distinct voice and that there is not too much crosstalk or overlapping speech.
can I get timestamps?
Every transcript includes word-level timestamps. In the SHRP viewer, you can see when each segment starts. If you need timestamps for video captioning, export as SRT or VTT and the timecodes are formatted automatically. The JSON export gives you full word-by-word timing data, which is useful if you are building something programmatic like a podcast player with synchronized text. Timestamps are accurate to within a fraction of a second.
how long does it take?
Processing time depends on the length of your episode. A 30-minute podcast typically takes 2 to 4 minutes. A full hour-long episode finishes in about 4 to 7 minutes. Most of that time is the AI model processing the audio, not the upload. You will see a progress indicator while it runs. The upload itself depends on your internet connection, but podcast MP3 files are usually in the 30 to 90 MB range, which uploads quickly on any modern connection.
is it accurate enough to publish?
For well-recorded podcasts with clear audio, SHRP delivers roughly 95 to 98 percent accuracy. That is close to human-level for standard conversational English. Proper nouns, brand names, and technical jargon are where errors tend to appear. SHRP includes a confidence heatmap that color-codes low-confidence words so you know exactly where to review. For accessibility compliance or formal publishing, you should do a quick read-through and fix any highlighted sections. For show notes or internal use, the raw transcript is usually good enough as-is.
what does it cost?
SHRP has a free 15-minute file upload trial so you can test accuracy on your own audio before committing. Voice typing in the browser is always free with no limits. For regular podcast episodes, the Starter plan at $3 per month covers most workflows. If you produce multiple shows or long-form episodes and need higher upload limits, the Pro plan at $6 per month is built for that. There are no per-minute charges, no surprise fees, and no annual contract required.
can I edit the transcript?
You can review and copy your transcript directly in the SHRP viewer. The confidence heatmap highlights words the AI was uncertain about, so you can jump straight to the parts that need attention rather than reading the entire thing. You can export the transcript as TXT, SRT, VTT, DOCX, or JSON and edit in whatever tool you prefer. Saved transcripts are available in your transcription history so you can come back to them anytime.
what about show notes?
Once you have a transcript, you can use SHRP's smart voice tools to extract structured content from it. Generate a summary of the episode, pull out key names and dates mentioned, or create a list of action items and topics covered. This is useful for writing episode descriptions, creating blog posts from interviews, or building a searchable archive of your podcast content. The extraction runs on top of your existing transcript so there is no additional upload or processing time.
ready to transcribe your next episode?