Edit Podcasts with Skrrol AI
Audio-first workflow with EQ, noise reduction, captions, and a visualizer track for video podcasts.
Podcasts are an audio-first medium that increasingly ships as video too. Skrrol AI handles both. The audio mixer gives you per-track EQ, compression hooks, and noise reduction. The multi-track timeline supports a host track, multiple guest tracks, an intro/outro music bed, and SFX — each treated independently. The subtitle generator transcribes the entire conversation for show-notes use and for captioned video podcast distribution.
The podcast editing workflow has its own rhythm. You start with raw recordings — host on track 1, each guest on a separate track, intro music on a final track. Sync them by waveform if you recorded across separate devices. Then the cleanup pass: noise reduction on every track to remove room hum and breath noise, EQ to give each voice its own frequency space, level normalization so no one clips and no one disappears.
Next is the conversational edit. Trim long pauses, remove filler words ('um', 'uh', 'like') with the razor tool, and ripple-delete to keep the conversation flowing. Most podcast editors aim to compress a 90-minute raw recording into a 60-minute finished cut — about 33% efficiency. Skrrol's multi-track timeline keeps every speaker's track aligned through ripple-deletes so you don't break sync.
For video podcasts, the visualizer track turns the audio into something watchable. Skrrol supports a simple waveform or frequency-bar visualizer that animates with the audio. Combined with face-cam recordings of each speaker (typically displayed as a grid layout via picture-in-picture), the video version is easy to assemble on top of the audio edit.
Intros and outros are formulaic. A 15-second pre-roll intro with a music bed and a host name overlay; a 30-second post-roll outro with a CTA, sponsor read, and music bed. Skrrol's animated-titles handle the typography. The audio mixer ducks the music bed under the host's voice automatically.
Exports cover audio (WAV master, MP3 for distribution platforms like Spotify and Apple Podcasts) and video (1080p H.264 for YouTube and Spotify video, 9:16 social clips for promotion).
Platform specs
| Dimension | Value |
|---|---|
| Audio format | WAV master at 48kHz/24-bit; MP3 192–320kbps for distribution |
| Audio loudness | -16 LUFS for podcasts (Apple/Spotify standard) |
| Video aspect ratio | 16:9 for YouTube/Spotify video; 9:16 for promo clips |
| Length | 20–90 minutes typical |
| Captions | Strongly recommended for video podcasts |
| Layout | Grid of face-cams + visualizer for video version |
Workflow — idea to export
- 1
Import host and guest tracks
Each speaker on a separate audio track. Sync by waveform if recorded on separate devices.
- 2
Apply noise reduction and EQ
Per-track noise reduction removes room hum. EQ gives each voice its own frequency space.
- 3
Remove filler words
Razor and ripple-delete to remove 'um', 'uh', long pauses. Multi-track ripple keeps sync.
- 4
Add intro / outro
Pre-roll with music bed and host name overlay. Post-roll with CTA and sponsor read.
- 5
Caption the conversation
Subtitle generator transcribes the whole episode. Use for show notes and burned-in video captions.
- 6
Build the video version (optional)
Drop face-cam recordings into a grid layout via PiP. Add a visualizer track for audio-only segments.
- 7
Export audio and video masters
WAV / MP3 for podcast platforms; 1080p H.264 for YouTube; 9:16 cuts for social promo.
Recommended Skrrol Features
Editor capabilities tuned for this use case.
Recommended Generators
AI generation tools that pair with this workflow.
Who this is for
Interview podcast
60-minute weekly interview with host and guest, video edition with face-cam grid.
Solo podcast
30-minute solo episode with intro/outro and music bed under.
Roundtable podcast
75-minute multi-host roundtable with 4 audio tracks and video face-cam grid.
Promo clip
60-second vertical promo cut from a long episode for TikTok / Reels distribution.
Frequently asked questions
Can Skrrol handle multi-track audio?
Yes. Each speaker gets a separate audio track with independent EQ and noise reduction.
What's the standard podcast loudness?
-16 LUFS integrated for Apple Podcasts and Spotify (slightly hotter than YouTube's -14 LUFS).
How do I make a video version?
Drop face-cam recordings into a PiP grid layout and add a visualizer track for audio-only segments.
Should I burn captions in for the video?
Yes — most podcast video viewers on YouTube and Spotify Video watch with captions on.
Can I use AI voiceover for intros?
Yes — text-to-speech generates broadcast-quality intros for promo or ad reads if you don't want to re-record.
Related use cases
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