I made a website for searching police scanner transcripts

Hacker News

Hey everyone, copcrawler.com is a website that lets you search through transcribed police scanner audio from broadcastify.com. I'm currently using faster-whisper with the tiny.en model to transcribe audio from about 14 departments on some old laptops. The transcript quality is relatively low however it's good enough to find common police scanner keywords like 'shots fired' or 'burglary'. I've also implemented RAG for a of couple departments which you can try out with the chat bot mode.

Visit product View on Hacker NewsAug 23, 2024

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5points

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Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, tiny, using · Missing: mac, agents, macos

62%62% 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.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

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

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Strong signals: scanner · 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

52%52% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

43%43% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

11%11% 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

10%10% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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