Raspberry Pi Voice-Interactive Robot
Budget: ₹1,500 – ₹12,500 INR
I want to turn a Raspberry Pi 4 or 5 into a fully offline, multilingual, voice-interactive robot that can understand and speak English, Bengali, Hindi, and Nepali.
The hardware (Pi, mic array, speaker, power supply, and a basic robot chassis) is already on my bench.
What I need from you is the software stack and setup guidance, so I can flash an SD card, plug everything in, and start talking to it immediately.
⸻
Core Experience
The robot should support natural, low-latency conversation triggered by a wake-word (e.g., “Hey Pi”).
I prefer open-source solutions but I’m open to paid APIs if latency remains low and the system still functions when offline or the internet drops.
Possible tech options include:
• Python / Rasa / Rhasspy
• Vosk / Whisper / DeepSpeech (for speech-to-text)
• TensorFlow / PyTorch (for custom intent models)
• eSpeak / Coqui TTS / Piper (for text-to-speech)
⸻
Deliverables
1. Complete codebase with:
• Wake-word detection
• Speech-to-Text (multilingual)
• Intent handling (basic conversational logic)
• Text-to-Speech for all four languages
2. Installation script or Dockerfile that sets up every dependency on a fresh Raspberry Pi OS image.
3. Configurable “skills” framework so I can later add new modules (e.g., home-automation, information queries, or small-talk) without rewriting the core.
4. README / Documentation explaining setup, configuration, and how to extend intents and responses.
5. One live test session (screen-share) where we confirm:
• The Pi hears me clearly from 2–3 meters away
• Average response time ≤ 2 seconds
• Multilingual detection + reply works correctly
⸻
Acceptance Criteria
✔ The live demo works end-to-end as above.
✔ I can re-flash the SD card and reproduce the setup unassisted using your documentation.
✔ Speech and responses remain functional even with no internet connection.
⸻
What to Include in Your Proposal
When you respond, please outline:
• Which libraries or frameworks you’d use and why they’re suitable for multilingual use on Raspberry Pi.
• How you’ll handle offline fallback and language switching.
• Any similar projects you’ve delivered (voice assistants, chatbots, or Raspberry Pi AI builds).
The hardware (Pi, mic array, speaker, power supply, and a basic robot chassis) is already on my bench.
What I need from you is the software stack and setup guidance, so I can flash an SD card, plug everything in, and start talking to it immediately.
⸻
Core Experience
The robot should support natural, low-latency conversation triggered by a wake-word (e.g., “Hey Pi”).
I prefer open-source solutions but I’m open to paid APIs if latency remains low and the system still functions when offline or the internet drops.
Possible tech options include:
• Python / Rasa / Rhasspy
• Vosk / Whisper / DeepSpeech (for speech-to-text)
• TensorFlow / PyTorch (for custom intent models)
• eSpeak / Coqui TTS / Piper (for text-to-speech)
⸻
Deliverables
1. Complete codebase with:
• Wake-word detection
• Speech-to-Text (multilingual)
• Intent handling (basic conversational logic)
• Text-to-Speech for all four languages
2. Installation script or Dockerfile that sets up every dependency on a fresh Raspberry Pi OS image.
3. Configurable “skills” framework so I can later add new modules (e.g., home-automation, information queries, or small-talk) without rewriting the core.
4. README / Documentation explaining setup, configuration, and how to extend intents and responses.
5. One live test session (screen-share) where we confirm:
• The Pi hears me clearly from 2–3 meters away
• Average response time ≤ 2 seconds
• Multilingual detection + reply works correctly
⸻
Acceptance Criteria
✔ The live demo works end-to-end as above.
✔ I can re-flash the SD card and reproduce the setup unassisted using your documentation.
✔ Speech and responses remain functional even with no internet connection.
⸻
What to Include in Your Proposal
When you respond, please outline:
• Which libraries or frameworks you’d use and why they’re suitable for multilingual use on Raspberry Pi.
• How you’ll handle offline fallback and language switching.
• Any similar projects you’ve delivered (voice assistants, chatbots, or Raspberry Pi AI builds).
Related categories:
Python
Translation
Audio Services
Voice Talent
Raspberry Pi
Documentation
Deep Learning
Natural Language Processing