EraseNoise
Clears steady background noise from speech in audio and video
AI & Machine Learning·Productivity
What is EraseNoise?
EraseNoise removes steady background noise from speech in audio and video. Drop in a recording and it clears fans, hum, hiss, and room tone while keeping the voice intact. It is made for podcasts, interviews, calls, tutorials, and voiceovers. The free tier handles everyday clips. Pro is about $9.99 a month when you need more. Open a file, let EraseNoise pull the noise out, and export speech you can publish.
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FounderPlaybooks.
What other founders did to grow.
2722 dispatches from hundreds of founders, pulled from the week's best podcasts.
Lou I've seen your some of your tweets about real estate would you like to teach a class I never thought about teaching a class on real estate and then after I did the classes I thought wait maybe I could like take the transcript from these classes put it into a book and make a few dollars outside the community
Teach an internal class first, then ship the transcript as a book
Louie's real-estate book was pulled out of him: a community peer saw his tweets and asked him to run a guest class, the transcript became a book, and the book sold outside the community. One input compounds into multiple assets — live audience validates the material, transcripts become the product, the product seeds the next thing.
We try to figure out what is the right level of investment on the digital upper funnel campaigns — how do these impact our performance campaign. You can actually do this very easily with a conversion lift study through Meta among other partners.
Conversion lift studies prove how much upper-funnel brand spend boosts performance campaigns
One of the hardest questions in mixed brand/performance budgets is proving the causal link between upper-funnel spend and downstream conversions. Meta's conversion lift study (and equivalents from other platforms) shuts down specific audiences temporarily to measure the counterfactual. At Deezer, this validated assumptions at a much larger magnitude than last-click attribution ever showed.
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