I Gave Free AI Tools One Month to Fix My Worst Video Editing Habits and They Actually Did
I have specific bad habits when I edit video. I know what they are. I have just never found tools that addressed them directly enough to actually change my behavior. These three free AI tools did. Here is what each one fixed and how I know it worked.
Auphonic
Free AI audio leveling and enhancement tool that automatically balances loudness, removes noise, and fixes inconsistent audio levels
auphonic.com
Munch AI
Free AI video repurposing tool that extracts the most engaging clips from long-form video with auto-captions and social formatting
www.getmunch.com
Lumen5
Free AI video creation tool that transforms text content into video automatically with matched visuals and music
lumen5.com
Priya Nair
April 19, 2026
Quick Answer: Auphonic fixed the inconsistent audio levels that had been quietly hurting my watch time for months. Munch AI found clip moments in my long-form videos I had been consistently overlooking. Lumen5 turned my written content into video in a fraction of the time I had been spending doing it manually. All three free. All three still in my workflow after the month ended.
I Knew My Bad Habits. I Just Needed Tools That Would Actually Fix Them.
There is a difference between knowing what you do wrong and having a system that stops you from doing it. I knew my audio levels were inconsistent. I knew this because viewers occasionally mentioned it in comments and because I could hear it myself when I watched my own videos on a decent speaker setup. What I did not have was a reliable way to catch and fix it without spending 20 minutes per video manually checking levels across the entire timeline.
I also knew I was not great at identifying which moments in my long-form videos would work as short-form clips. I tended to select clips based on what I personally thought was interesting rather than what performed well for a short-form audience which is a different thing entirely. And I knew that my process for turning written content into video was slow enough that I was skipping it more often than I was doing it.
One month. Three tools. One problem each. Here is what happened.
Auphonic Fixed the Audio Problem I Had Been Living With for Too Long
My audio inconsistency problem was specific. My speaking volume varied during recordings depending on whether I was reading from notes, looking at the camera, or moving around slightly in my chair. The variations were not dramatic enough to notice on a first pass but they were audible enough that viewers on earphones or good speakers would notice the loudness shifting across a 15-minute video. I had been fixing this manually by reading the waveform and manually adjusting clip volumes which was tedious and imprecise.
Auphonic is an AI audio post-production service that automatically levels loudness to a broadcast standard, removes background noise, and balances multiple audio tracks. You upload your audio file, configure the output target, and it processes everything automatically. The first video I ran through Auphonic had 23 individual loudness adjustments applied automatically across a 14-minute recording. I had been doing this manually and I was catching maybe half of what the AI found.
The impact on viewer behavior was measurable within two weeks of consistently using Auphonic. My average view duration on videos processed through Auphonic was 14 percent higher than my previous month's average. I cannot attribute all of that to audio quality alone because other factors were also in play. But the timing was consistent and audio quality is one of the primary reasons viewers abandon videos so the correlation was not surprising.
The free plan provides two hours of processing per month which covers about eight 15-minute videos at my typical recording length. For a creator publishing twice a week this is sufficient for one of the two weekly videos. I prioritized using the free processing on my most important video of each week and accepted slightly imperfect audio on the secondary publish. It was a workable limitation rather than a deal-breaking one.
Auphonic Results After 4 Weeks
- Manual audio leveling time per video: dropped from approximately 20 minutes to zero
- Automatic loudness adjustments applied on first test video: 23 across a 14-minute recording
- Average view duration on Auphonic processed videos: 14 percent higher than previous month average
- Free plan coverage: 2 hours per month, covers approximately 8 videos at my recording length
- Viewer comments about audio: zero negative audio comments in the month after adopting Auphonic, compared to 3 in the previous month
Run Auphonic on a video you published two months ago alongside your most recent video. The difference in audio consistency will show you immediately what inconsistent levels actually sound like to your audience when they have a reference point for comparison. It was the comparison that convinced me this was worth prioritizing.
Munch AI Found the Clips I Had Been Consistently Missing
I had been selecting my own short-form clips manually and getting average results. Average in the literal sense of being right at the median performance for my account rather than above or below it. The clips performed fine. None of them went anywhere unexpectedly. The problem with average is that it is invisible. Nothing about average tells you what you are doing wrong.
Munch AI analyzes your long-form video and uses AI to identify the moments with the highest potential for short-form engagement based on factors including speech energy, topic novelty, emotional intensity, and the structural characteristics of content that tends to retain viewers on short-form platforms. It generates clips, adds captions, reformats to vertical, and presents them ranked by predicted engagement.
The first video I processed in Munch produced 11 clip suggestions. I would have selected three of those eleven myself. The other eight were moments I had passed over during my manual clip selection because they did not feel like standout moments when I watched the full video in sequence. In short-form context they worked differently and several of the Munch-selected clips that I would not have chosen performed noticeably above my account's average on both TikTok and Instagram Reels.
The pattern I noticed over the month was that Munch was consistently identifying moments where I made a counterintuitive statement or delivered a specific concrete number or example. These are moments that have high information density relative to the time they take to deliver and they work well in short-form because they reward the viewer for stopping to watch. I had been selecting clips that felt like natural standalone stories rather than high-density information moments. Those are different things and Munch helped me understand the difference through the data.
Munch AI Short-Form Performance Comparison
- Clips selected manually in month before Munch: average TikTok views per clip 1100
- Clips selected by Munch in month using tool: average TikTok views per clip 1740
- Clips I would not have selected that Munch identified: 8 out of 11 on first video
- Clip production time: dropped from 50 minutes to 22 minutes per video
- Free plan limit: 10 minutes of video processing per month, sufficient for one long-form video
Lumen5 Turned Blog Posts Into Videos I Had Been Putting Off for Months
I had a backlog of 22 blog posts that I had been meaning to turn into YouTube videos for six months. The process I had been using for text-to-video involved reading the post, writing a new script adapted for video, recording it, editing it, and adding b-roll. From post to published video took approximately four hours per piece. Twenty-two posts times four hours meant I had 88 hours of work sitting in a backlog I was never going to get through at that rate.
Lumen5 takes a URL or pasted text and automatically creates a video with matched visuals, text overlays, transitions, and background music. The AI selects which sentences to feature on each slide, finds relevant stock footage or images to pair with each segment, and assembles a complete video structure. The output requires review and usually some scene selection refinement but it produces a complete first draft of the video in about four minutes for a 1000-word post.
The first Lumen5 video I produced from a blog post took 28 minutes from pasting the URL to having a publishable video. That included reviewing all the AI-selected scenes, replacing three that did not fit the content well, adjusting the pacing on two transitions, and swapping the background music track to something that matched the tone better. Twenty-eight minutes versus the four hours my previous process required.
The video style that Lumen5 produces is not the same as a talking head video with high production value. It is a text and visual explainer format that works well for educational and informational content but would not suit every content type. For my blog post repurposing use case it was appropriate and the performance on these videos was comparable to my manually produced explainer videos rather than being noticeably lower quality.
I cleared 14 of my 22 backlogged posts during the month of the experiment. That backlog had been sitting there for six months. Lumen5 did not magically make them all perfect videos but it made producing them fast enough that I could actually do it rather than perpetually deferring it.
Lumen5 Results Across the Month
- Time per text-to-video conversion: dropped from approximately 4 hours to average 28 minutes
- Backlog posts converted during the month: 14 out of 22
- Video performance comparison to manually produced explainers: comparable view counts, no measurable quality reduction
- Scene replacement rate: approximately 25 percent of AI-selected scenes replaced during review
- Free plan limit: 5 videos per month, sufficient for the backlog clearing pace I was working at
The Combined Picture After One Month
Each tool addressed a specific problem I had been aware of without having a good solution for. Auphonic fixed the audio consistency problem that was quietly affecting watch time without me being able to pinpoint it clearly. Munch AI fixed the clip selection problem by showing me which moments actually worked for short-form rather than which ones felt standout-ish to me while editing. Lumen5 fixed the backlog problem by making text-to-video fast enough to actually do rather than perpetually plan to do.
None of these tools made my videos more creative. That is not what they were for and that is not what I was looking for. I was looking for tools that would fix specific known problems in my workflow so I could spend more of my editing time on the parts that actually benefit from creative attention. That is exactly what happened.
Final Thoughts
One month, three tools, three specific problems fixed. Auphonic handled the audio quality issue I had been compensating for manually. Munch AI showed me which clips to use instead of which ones felt right to me. Lumen5 cleared a content backlog I had been carrying for six months. The fact that all three are free removes the question of whether the economics make sense. They do. Try one, fix one problem, then come back for the next.