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I Built Smart Radio That Auto-Skips Talk and Ads by Using ML

I Built Smart Radio That Auto-Skips Talk and Ads by Using ML

by FreeGuessr·Feb 27, 2026·5 points·4 comments
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AI Analysis

●●SolidEye CandySolve My Problem

Global radio map with browser-side ML ad-skip beats obvious, but streaming radio already solved.

Strengths
  • •In-browser ML inference on audio streams avoids server processing and privacy concerns entirely.
  • •WebGL rendering 70K stations across 11K locations with real-time user activity—genuinely smooth map tech.
  • •Physical media key support and sensitivity slider make the skip behavior configurable without server calls.
Weaknesses
  • •Ad-detection relies on speech classification; music with talk (DJ mixes, podcasts) gets false-positive skips.
  • •Competes with existing radio apps (TuneIn, RadioGarden) that don't require browser—unclear sustained advantage.
Category
Open Source
Target Audience

Radio listeners, privacy-conscious users, casual music streamers

Similar To

RadioGarden · TuneIn · Podcast apps with auto-skip

Post Description

Hi, I built TuneJourney to solve a specific annoyance: radio ads and DJ chatter. The core feature is an in-browser "AI Skip Talk" filter.

The Tech: Instead of processing on a server, it uses the Web Audio API to capture the stream locally and runs a lightweight ML classification model directly in your browser. It estimates the music vs. speech probability in near real-time. If enabled, it automatically triggers a "next" command to hop to another station the moment an ad, news segment, or DJ starts talking.

Features: - In-browser Inference: Entirely local and privacy-focused; no audio data ever leaves your machine. - WebGL + Point Clustering: Renders 70,000 stations across 11,000 locations smoothly. - Real-time Activity: See other users on the globe and what they are listening to in real-time. - System Integration: Full Media Key support for physical keyboard and system-level Next/Prev buttons. - Customization: Includes a talk sensitivity slider for the ML model so you can tweak the threshold.

Check it out: https://tunejourney.com

Let me know what you think! I am interested if this project is worth further investment, building a mobile app, etc.

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