Introduction: AI Powered Bull**** Detector
The one device we all need, an AI Powered Bull**** Detector!
- Raspberry Pi
- NeoPixel Ring
- 3D Printer
- Pi Camera
- AIY Kit
- Google Dialogflow
Step 1: Project Video
Step 2: 3D Printing
First things first, we need a container. In this case we chose to 3D print a nice colorful one. You can also use something else, as long as all the electronics fit.
All the model files are attached.
Step 3: Electronics
It all starts with a Raspberry Pi 3B+.
Because we want to use Speech-To-Text we also have to add an AIY VoiceHat and the corresponding microphone. It's all documented right here.
Last but not least, we wire up the NeoPixel ring, here's a great tutorial for just that.
With everything set up we can test out the Speech-To-Text and NeoPixel ring, the test code is attached.
Step 4: Training the AI - Dialogflow
For our AI we are going to use Dialogflow. Originally, it's meant to be used as chatbot software, we can slightly misuse it to train our bull**** detector.
We create two intents, one is our fallback, and the other bull****. Next we add all the content in the training phrases of our bull**** intent. You can really go nuts here.
After saving, our bot will be training to detect bull**** based on the given training phrases. Once done, we can use a bit of python code to connect to our freshly trained AI.
The data flow is as followed:
- The microphone picks up someone speaking and records it.
- This file is sent to the Google Cloud and transformed into text.
- The generated text is sent back to the Raspberry Pi.
- This text is then sent to Dialogflow.
- Dialogflow tries to match the text with the content from our bull**** intent, and depending on the result it will either send back the bull**** intent or the default fallback one.
- On our Pi we check the name of the intent, and if it's 'Default Fallback Intent' we tell the lights to flash green, meaning no bull***. Otherwise we flash red, indicating bull****.
The full code is attached.
Step 5: Remo.tv
We can't keep something so powerful all to ourselves! So, we are going to make our detector available for everybody. To make this happen we are going to use Remo.tv, a robot streaming platform. All we need to do is attach a Pi Camera and follow their setup instructions.
Once Remo.tv is set up, we will write our own chat handler. Instead of using Speech-To-Text we directly send the chat messages we receive on Remo.tv to Dialogflow. The rest of the logic remains the same. Just add a note in the background to tell visitors what they are looking at, and we're all done.
Step 6: Result!
We successfully built a AI powered bull**** detector, which can learn from new input!
You can try it out yourself right here.
Now, where can we collect our nobel peace prize?
Participated in the
Raspberry Pi Contest 2020