How to Turn Your Raspberry Pi into Amazon Echo (Alexa) for $15

This guide demonstrates converting a Raspberry Pi into an Alexa-powered device. The setup is fairly straightforward and completable within an hour at minimal cost by repurposing existing peripherals.

Hardware Requirements

• Raspberry Pi 3 (or compatible earlier model)
• 8 GB SD Card with Raspbian (Jessie)
• Micro-USB power cable
• 3.5mm speaker (Bluetooth or wired)
• USB microphone or equivalent
• Keyboard, display, and mouse for setup

Estimated Cost: Under $59 total (Pi: $39, speaker: $8, camera/mic: $7)

Installation Steps

Step 1: Raspberry Pi Setup

Configure Raspberry Pi with Raspbian, connect peripherals, and configure audio. Adjust microphone levels using the alsamixer command and modify /usr/share/alsa/alsa.conf to set default audio devices.

Step 2: Amazon Developer Account

Register for an Amazon Developer account, navigate to Alexa Voice Service, register a device type, and obtain Client ID and Client Secret credentials. Configure Web Settings with allowed origins: https://localhost:3000

Step 3: Install Alexa

Clone Amazon's sample application repository, edit automated_install.sh with ProductID, ClientID, and ClientSecret, then execute the installation script (30-45 minutes).

Step 4: Run Companion Service

cd ~/Desktop/alexa-avs-sample-app/samples/companionService && npm start

This starts the gateway service listening on Port 3000.

Step 5: Authenticate Account

Launch the client application via mvn exec:exec, authenticate through browser, and obtain device tokens for server communication.

Step 6: Enable Wake Word Detection

cd ~/Desktop/alexa-avs-sample-app/samples/wakeWordAgent/src && ./wakeWordAgent -e sensory

Troubleshooting

Common issues include:

• Authentication errors: Incorrect credentials
• Build failures: Missing dependencies
• Timeout exceptions: Network issues
• Microphone problems: Configuration issues

Advanced Implementation

Create bash scripts for automatic startup and integrate iOS/Android companion applications for custom skill development. You can also add wake word detection using Sensory or other providers.