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SpokenBits – Listen to your web content anywhere

Hacker News

SpokenBits – Listen to your web content anywhere

If you like reading content on the web, and sometimes is hard to catch up to your queue of articles and blog posts, you might find useful to have SpokenBits to read them for you while you are commuting, working out or simply cooking or cleaning the house. You will be able to conveniently add as many articles as you need and group them into collections (example: news, health, politics, etc). SpokenBits will extract the uncluttered relevant content, and will read it for you in its original language with minimal text ads or irrelevant information. Among other things, SpokenBits will keep track of unread/read articles, and listening progress. A convenient table of content is automatically created for each article for easy navigation. Personally, I've been using it to keep up to date during my commute by listening to the articles and blog posts that interest me. This is just the beginning, the SpokenBits team is working hard to bring the Audio Book experience to a broad range of Web Content, stay tuned. http://www.spokenbits.com

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Actual performance

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2comments
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting
65%65% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: new, using · Missing: mac, agents, macos
65%65% predicted probability of success on Product Hunt, 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.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs
37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · 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.

Correct prediction on native model

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