Turn Audio into Branded Video
Upload a podcast episode, webinar recording, or voice memo. ngram transcribes the audio, builds visual scenes synchronized to the content, and exports branded video with captions.
- Upload any audio file and get a branded video in under 5 minutes
- AI transcribes and builds visual scenes matched to spoken content
- Export as 16:9, 1:1, or 9:16 with auto-generated captions
audio to video
Any audio
MP3, WAV, M4A, podcast, or recording
Auto-caption
Transcription and branded captions included
Under 5 min
From audio file to branded video export
Trusted by teams at
To convert audio to video, upload your MP3, WAV, or audio recording to ngram. The AI transcribes the content, identifies key moments and topic shifts, then generates visual scenes synchronized to the spoken content. Captions are styled to your brand automatically. The process takes under 5 minutes from upload to export.
Audio content is invisible on video-first platforms
You recorded a great podcast episode. The insights are quotable, the guest said memorable things, and the content would resonate on LinkedIn and YouTube. But both platforms prioritize video. An MP3 link in a post gets scrolled past. A video clip with captions gets watched, shared, and commented on.
ngram converts audio to branded video with captions in under 5 minutes.
How it works
Upload your audio file
Drag and drop an MP3, WAV, M4A, or any common audio format up to 500 MB.
ngram transcribes and plans scenes
The AI transcribes the audio, identifies key moments and topic shifts, and builds a visual storyboard synchronized to the spoken content.
Review and adjust the storyboard
See every scene with its caption and visual treatment. Trim sections, highlight quotes, or adjust the visual style per scene.
Export your branded video
Download in 16:9 for YouTube, 1:1 for LinkedIn, or 9:16 for Reels and TikTok. Captions and brand elements included.
Who is this for
Content Creators
Turn podcast episodes into video clips for YouTube, LinkedIn, and social
See solutionProduct Marketers
Convert webinar recordings into shareable video highlights for campaigns
See solutionWhen to use this
Marketing has a podcast episode and wants video clips for LinkedIn and YouTube
→ Upload the MP3, ngram transcribes and builds visual scenes, export clips in 3 formats
View use caseDevRel recorded a conference talk and needs a 2-minute branded recap video
→ Upload the audio, review the AI-selected highlights, export a branded recap
View use caseSales has a recorded customer call with a testimonial moment worth sharing
→ Upload the audio clip, ngram builds a visual testimonial video with captions
View use caseWhat goes in, what comes out
Source input
Audio File
Size limit: Up to 500 MB per file
Clear speech with minimal background noise produces the best transcriptions and scene breaks. Professional recordings and studio audio work best. Phone recordings still work but may need manual storyboard adjustments.
Output
Length: 15 seconds to 10 minutes
Formats
Resolutions
Export as
How ngram compares to Headliner, Descript, Kapwing
| Feature | ngram | Manual | Headliner, Descript, Kapwing |
|---|---|---|---|
| Time to finished video | Under 5 minutes from upload | ||
| Visual scene generation | AI builds scenes matched to spoken content and topic shifts | ||
| Brand consistency | Brand Kit applied to every scene and caption | ||
| Transcription accuracy | AI transcription with caption sync | ||
| Multi-format export | 16:9, 1:1, 9:16 from one audio file | ||
| Text-based editing | Scene-level editing via storyboard | ||
| Captions | Auto-generated, styled to brand, burn-in or separate |
Audio to video conversion gives spoken content a visual layer for platforms where video outperforms audio by 5-10x in engagement. Podcast episodes, webinar recordings, conference talks, and voice memos all contain valuable content trapped in a format that social platforms deprioritize in their algorithms.
How ngram converts audio to video
ngram transcribes the audio, identifies key moments and topic shifts, and generates visual scenes synchronized to the spoken content. Captions are added and styled to your brand. The AI distinguishes between narrative sections, quotable moments, and transitions to vary the visual treatment throughout the video - not a static waveform over a single background image.
Podcast repurposing at scale
A single podcast episode can produce 5-10 video clips for social. ngram identifies the most quotable segments and builds standalone clips that work without the full episode context. Each clip gets its own storyboard, branded visuals, and captions - ready to post on LinkedIn, YouTube Shorts, Instagram Reels, or TikTok.
Supported audio formats and quality tips
ngram accepts MP3, WAV, M4A, AAC, OGG, and FLAC files up to 500 MB - covering most podcast episodes, webinar recordings, and meeting recordings. Clear speech with minimal background noise produces the best transcriptions and most accurate scene breaks. Professional podcast recordings and studio-quality webinars work best. Phone recordings still work but may need storyboard adjustments where transcription missed a word.
Audio to video vs audio visualization tools
Most audio-to-video tools place a waveform animation or audiogram over a static background image. The result is technically a video but visually monotonous. ngram builds distinct visual scenes for each segment of the audio - topic shifts get new scene treatments, quotes get callout cards, and transitions between speakers get visual breaks. The output looks like a produced video, not a static image with a bouncing waveform.
Ready to turn your audio into video?
Upload your recording and see the storyboard in seconds. No video editing experience needed.
No credit card required - Works with MP3, WAV, M4A, and more