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Detects reggaeton genre with Machine Learning and sends packets to disable BT speakers (hopefully)
| Date | Stars |
|---|---|
| 2026-08-04 | 999 |
| 2026-08-06 | 1000 |
| 2026-08-07 | 1001 |
| 2026-08-13 | 1001 |
| 2026-08-14 | 1001 |
| 2026-08-16 | 1002 |
| 2026-08-17 | 1003 |
| 2026-08-18 | 1003 |
| 2026-08-23 | 1004 |
| 2026-08-27 | 1005 |
| 2026-08-29 | 1006 |
| 2026-09-02 | 1005 |
| 2026-09-04 | 1006 |
| 2026-09-05 | 1007 |
| 2026-09-06 | 1008 |
| 2026-09-09 | 1009 |
| 2026-09-12 | 1009 |
| 2026-09-23 | 1009 |
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| 2026-09-30 | 1012 |
| 2026-10-03 | 1012 |
| 2026-10-06 | 1013 |
| 2026-10-13 | 1014 |
| 2026-10-18 | 1015 |
| 2026-10-23 | 1016 |
| 2026-10-24 | 1017 |
| 2026-10-27 | 1018 |
| 2026-10-29 | 1019 |
| 2026-11-03 | 1020 |
| 2026-11-04 | 1020 |
Today
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Momentum
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# 🎧🚫 Reggaeton Be Gone
### Edge Machine Learning device that recognizes reggaeton and triggers a Bluetooth test routine on a configured speaker
[](https://www.raspberrypi.com/products/raspberry-pi-3-model-b/)
[](https://edgeimpulse.com/)
[](https://www.python.org/)
[](https://huggingface.co/ronibandini/reggaetonbegone)
[](LICENSE)
[](https://github.com/ronibandini/reggaetonBeGone/stargazers)
**Roni Bandini — Buenos Aires, Argentina — February 2024**
**Reggaeton Be Gone** is an experimental Raspberry Pi device inspired by **TV-B-Gone**.
It continuously samples ambient audio, uses an **Edge Impulse audio-classification model** to determine whether reggaeton is playing, displays the inference confidence on a 128×32 OLED, and—when the configured threshold is exceeded—triggers a Bluetooth test routine against a configured speaker.
The original motivation was simple: a neighboring Bluetooth speaker playing loud reggaeton every morning.
The resulting project combines:
* 🎙️ Audio acquisition
* 🧠 Edge Machine Learning
* 🎵 Music-genre classification
* 🍓 Raspberry Pi
* 📡 Bluetooth experimentation
* 🖥️ OLED feedback
* 📝 Event logging
---
## 🧷 Simpler Alternative: Pocket Gone
A later project explores the Bluetooth side without Machine Learning or a Raspberry Pi.
**Pocket Gone** is smaller, cheaper and portable:
👉 **[pocketgone.com](https://pocketgone.com/)**
The evolution from Reggaeton Be Gone to Pocket Gone was also presented at Nerdearla 2025:
👉 **[Pocket Gone — Nerdearla / NERDflix](https://nerdearla.com/nerdflix/BSzp_WEursA/)**
---
# 🏗️ Architecture
```mermaid
flowchart LR
MUSIC["🎵 Ambient Music"]
MIC["🎙️ USB Microphone"]
PI["🍓 Raspberry Pi 3"]
EI["🧠 Edge Impulse<br/>AudioImpulseRunner"]
CLASS{"reggaeton?"}
OLED["🖥️ 128×32 OLED"]
LOG["📝 log.txt"]
BT["📡 Bluetooth Test Routine"]
SPEAKER["🔊 Configured Speaker"]
MUSIC --> MIC
MIC --> PI
PI --> EI
EI --> CLASS
CLASS --> OLED
CLASS --> LOG
CLASS -->|"score > threshold"| BT
BT --> SPEAKER
```
The ML inference runs locally on the Raspberry Pi using an Edge Impulse `.eim` deployment.
---
# ✨ Features
* 🎵 Reggaeton / other-music classification
* 🧠 Edge Impulse Linux inference
* 🎙️ USB microphone or USB audio interface
* 🖥️ 128×32 SSD1306 OLED
* 🔘 Physical start button
* 🎯 Configurable inference threshold
* 📡 Configurable Bluetooth target
* 📝 Timestamped activity log
* 🔬 Multiple experimental Bluetooth methods
* 🧪 Manual `forceFire` test mode
* 🖼️ Custom OLED graphics and font
* 🧱 3D-printed front panel
* 🔄 Several later experimental versions
---
# 🧠 Machine Learning
The original model was trained because common music-genre datasets such as GTZAN did not provide a dedicated reggaeton class.
The workflow was:
```mermaid
flowchart LR
SONGS["🎵 Music Samples"]
WAV["WAV<br/>Mono / 16 kHz"]
SPLIT["✂️ 4 s Windows"]
MFE["🔬 MFE"]
NN["🧠 Classification"]
EIM["📦 Linux ARM .eim"]
PI["🍓 Raspberry Pi"]
SONGS --> WAV
WAV --> SPLIT
SPLIT --> MFE
MFE --> NN
NN --> EIM
EIM --> PI
```
Original settings documented for Version 1:
| Parameter | Value |
| ----------------- | -------------: |
| Audio | Mono WAV |
| Sample rate | **16 kHz** |
| Window size | **4000 ms** |
| Processing | **MFE** |
| Learning block | Classification |
| Target deployment | Linux ARM |
| Runtime format Excerpt of 19,744 characters
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:86fe36aab7640fbe, llm:Repository topics: 'machine-learning', 'music', 'bluetooth', 'ddos'. Description: 'Detects reggaeton genre with Machine Learning and sends packets to disable BT speakers (hopefully)'.
matched fp:86fe36aab7640fbe, llm:Repository topics: 'machine-learning', 'music', 'bluetooth', 'ddos'. Description: 'Detects reggaeton genre with Machine Learning and sends packets to disable BT speakers (hopefully)'.
matched fp:86fe36aab7640fbe, llm:Repository topics: 'machine-learning', 'music', 'bluetooth', 'ddos'. Description: 'Detects reggaeton genre with Machine Learning and sends packets to disable BT speakers (hopefully)'.