ToDiscuss – Voice chats with AI on topics from Twitter to learn English

Hacker News

Hi! I made a web app to practice English at advanced levels by having 2-way voice conversations with AI. But topics are taken from your Twitter followings section. Why I made this app? It's not hard to read documentations, or listen a podcast. But how about convince native speaker to change his mind in a discussion? Or jump into a group conversation and tell a story? This last mile of learning language is a pain. And it's my personal problem. Why Twitter? Twitter feed is a source of hot advanced topics in short form. And it is already customized to your specific interests. Such conversations give much more fun and benefits than discussing again and again boring general topics like "sports" or "movies". So the time spent on practice not feel wasted. Demo: https://www.loom.com/share/27e56e949449443194a387bffb3434f9 App: https://www.speakgpt.club/

Visit product View on Hacker NewsMar 30, 2023

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Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

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

53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

48%48% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

19%19% 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 · Missing: web3, crypto, cryptocurrency

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

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