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AI-Audiobook-Maker: Helping My Disabled Little Cousin Enjoy Story Books

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AI-Audiobook-Maker: Helping My Disabled Little Cousin Enjoy Story Books

Hey everyone! I've been working on a 'program"' (read as: overengineered bash script) It's called AI-Audiobook-Maker, and it was born out of my experiences with my 10-year-old cousin who is developmentally disabled. Despite his difficulties with reading, his enthusiasm for stories goes hard, even if he can't READ them. Watching him, I realized that the world of books was kinda out of reach for him, and I suppose many others. So, I set out to build something that could bridge this gap. After only finding shitty, expensive subscription sites that only gave you a couple hours of audio gen, I wanted to make it a bit more accessible. So I created a tool that can turn any text into a dope, natural sounding, engaging audiobook. Features that make it better than using ElevenLabs or something: - It does simple conversion of text files into audiobooks - You get a choice of six different voices and two models: tts-1 for faster processing and tts-1-hd for high-quality audio - Transparent and affordable pricing: only $0.015 per 1,000 characters I converted 'Fuzzing The Machine', a textbook on bug hunting, and that cost around $5. I've made it open-source in the hope that it can evolve and help more people. Would love to hear what you think, hopefully it can help you too. Audio Demo: https://voca.ro/1jrSMAA4WEsX P.S (Looking for a job rn, hmu at jack<at>jackdarcy.com.au> if you'd like to chat!

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting
98%98% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, model, models · Missing: agents, macos, agent
75%75% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
51%51% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: 000, io · Missing: https docs, excited, just released
47%47% 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
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat, audio · Missing: web3, crypto, cryptocurrency
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