DJ Fresh-voice-swap.ai: AI voices from Chart-Topping artists legally

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We’ve created a tool to allow people who can’t sing to create amazing sounding demos with the voices of hit maker artists legally with their permission. The platform enables you to record a demo directly on your phone or upload studio processed audio and get results in seconds. As music producers with over 5 million sales between us, and also engineers passionate about AI, when it comes to make a new tool we care about two things, high quality audio and the rights of artists. With all the horror stories about our favourite artists feeling ripped off we thought there has to be a better way! Your subscription directly supports the artists with whom we work closely to create precise vocal models. Our mission is to show that an AI product can be powerful and affordable for its users while still upholding ethical principles. #MusicAI #EthicalAI Producers, songwriters, singers — if you're seeking a way to streamline your creative process, 'Voice-Swap' is worth checking out. The platform allows you to generate convincing demos without the need for a studio setup. This tool can be particularly useful if you're composing for an artist with a distinctly different vocal style or if you're simply not a singer. For artists, 'Voice-Swap' opens up a new avenue for monetising your voice. You can decide whether your model is publicly or privately accessible, and our advanced technology ensures protection against piracy. We aim to make AI work for the artist. #AIThatWorksForArtists You can sign up at https://voice-swap.ai/ today for a 1-minute free demo voice and experiment with the bespoke models of our partner artists, including Angie Brown, Dominique Young Unique, Jamie McCool, or Nicky Ambers. We're constantly adding to our artist lineup, so stay tuned for updates. DJ Fresh & Nico Pellerin 2023

Visit product View on Hacker NewsJun 30, 2023

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TrustMRRFits verified-revenue profile · Strong signals: users, way · Missing: mobile apps, ios, personal

64%64% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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56%56% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io, including · Missing: https docs, excited, just released

40%40% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Strong signals: subscription · Missing: arr, mrr, revenue

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: audio · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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