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Hyper-Emotional AI Voice Acting for Anime and Movies

Hacker News

Hyper-Emotional AI Voice Acting for Anime and Movies

Hi HN, I’m using AI video generation to create anime and movies, but AI dubbing has been a major challenge. Most AI voices sound too flat and lack the emotional depth needed for voice acting, where dramatic expression is very important. That’s why I’m building this voice acting AI that lets you not only choose a voice but also control its emotion. In the Auto Emotion mode, you can include emotion hints in parenthesis to guide the speech generation. It’s still an early demo, but I’d love for you to try it out and share your feedback!

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Actual performance

6points
6comments
Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: using · Missing: mac, agents, macos
77%77% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
70%70% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: video · Missing: mobile apps, ios, personal
43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
39%39% 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 · Missing: https docs, excited, just released
36%36% 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 · Missing: arr, mrr, revenue
25%25% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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