pyr0ball
173f7f37d4
Ports prior voice assistant research and prototypes from devl/Devops into the Minerva repo. Includes: - docs/: architecture, wake word guides, ESP32-S3 spec, hardware buying guide - scripts/: voice_server.py, voice_server_enhanced.py, setup scripts - hardware/maixduino/: edge device scripts with WiFi credentials scrubbed (replaced hardcoded password with secrets.py pattern) - config/.env.example: server config template - .gitignore: excludes .env, secrets.py, model blobs, ELF firmware - CLAUDE.md: Minerva product context and connection to cf-voice roadmap
223 lines
6.4 KiB
Markdown
Executable file
223 lines
6.4 KiB
Markdown
Executable file
# K210 Performance Verification for Voice Assistant
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**Date:** 2025-11-29
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**Source:** https://github.com/sipeed/MaixPy Performance Comparison
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**Question:** Is K210 suitable for our Mycroft Precise wake word detection project?
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---
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## K210 Specifications
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- **Processor:** K210 dual-core RISC-V @ 400MHz
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- **AI Accelerator:** KPU (Neural Network Processor)
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- **SRAM:** 8MB
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- **Status:** Considered "outdated" by Sipeed (2018 release)
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---
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## Performance Comparison (from MaixPy GitHub)
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### YOLOv2 Object Detection
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| Chip | Performance | Notes |
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|------|------------|-------|
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| K210 | 1.8 ms | Limited to older models |
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| V831 | 20-40 ms | More modern, but slower |
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| R329 | N/A | Newer hardware |
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### Our Use Case: Audio Processing
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**For wake word detection, we need:**
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- Audio input (16kHz, mono) ✅ K210 has I2S
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- Real-time processing ✅ K210 KPU can handle this
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- Network communication ✅ K210 has ESP32 WiFi
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- Low latency (<100ms) ✅ Achievable
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---
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## Deployment Strategy Analysis
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### Option A: Server-Side Wake Word (Recommended)
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**K210 Role:** Audio I/O only
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- Capture audio from I2S microphone ✅ Well supported
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- Stream to Heimdall via WiFi ✅ No problem
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- Receive and play TTS audio ✅ Works fine
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- LED/display feedback ✅ Easy
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**K210 Requirements:** MINIMAL
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- No AI processing needed
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- Simple audio streaming
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- Network communication only
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- **Verdict:** ✅ K210 is MORE than capable
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### Option B: Edge Wake Word (Future)
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**K210 Role:** Wake word detection on-device
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- Load KMODEL wake word model ⚠️ Needs conversion
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- Run inference on KPU ⚠️ Quantization required
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- Detect wake word locally ⚠️ Possible but limited
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**K210 Limitations:**
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- KMODEL conversion complex (TF→ONNX→KMODEL)
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- Quantization may reduce accuracy (80-90% vs 95%+)
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- Limited to simpler models
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- **Verdict:** ⚠️ Possible but challenging
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---
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## Why K210 is PERFECT for Our Project
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### 1. We're Starting with Server-Side Detection
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- K210 only does audio I/O
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- All AI processing on Heimdall (powerful server)
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- No need for cutting-edge hardware
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- **K210 is ideal for this role**
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### 2. Audio Processing is Not Computationally Intensive
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Unlike YOLOv2 (60 FPS video processing):
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- Audio: 16kHz sample rate = 16,000 samples/second
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- Wake word: Simple streaming
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- No real-time neural network inference needed (server-side)
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- **K210's "old" specs don't matter**
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### 3. Edge Detection is Optional (Future Enhancement)
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- We can prove the concept with server-side first
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- Edge detection is a nice-to-have optimization
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- If we need edge later, we can:
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- Use simpler wake word models
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- Accept slightly lower accuracy
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- Or upgrade hardware then
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- **Starting point doesn't require latest hardware**
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### 4. K210 Advantages We Actually Care About
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- ✅ Well-documented (mature platform)
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- ✅ Stable MaixPy firmware
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- ✅ Large community and examples
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- ✅ Proven audio processing
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- ✅ Already have the hardware!
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- ✅ Cost-effective ($30 vs $100+ newer boards)
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---
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## Performance Targets vs K210 Capabilities
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### What We Need:
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- Audio capture: 16kHz, 1 channel ✅ K210: Easy
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- Audio streaming: ~128 kbps over WiFi ✅ K210: No problem
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- Wake word latency: <200ms ✅ K210: Achievable (server-side)
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- LED feedback: Instant ✅ K210: Trivial
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- Audio playback: 16kHz TTS ✅ K210: Supported
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### What We DON'T Need (for initial deployment):
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- ❌ Real-time video processing
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- ❌ Complex neural networks on device
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- ❌ Multi-model inference
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- ❌ High-resolution image processing
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- ❌ Latest and greatest AI accelerator
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---
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## Comparison to Alternatives
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### If we bought newer hardware:
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**V831 ($50-70):**
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- Pros: Newer, better supported
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- Cons:
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- More expensive
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- SLOWER at neural networks than K210
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- Still need server for Whisper anyway
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- Overkill for audio I/O
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**ESP32-S3 ($10-20):**
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- Pros: Cheap, WiFi built-in
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- Cons:
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- No KPU (if we want edge detection later)
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- Less capable for ML
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- Would work for server-side though
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**Raspberry Pi Zero 2 W ($15):**
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- Pros: Full Linux, familiar
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- Cons:
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- No dedicated audio hardware
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- No neural accelerator
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- More power hungry
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- Overkill for our needs
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**Verdict:** K210 is actually the sweet spot for this project!
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---
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## Real-World Comparison
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### What K210 CAN Do (Proven):
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- Audio classification ✅
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- Simple keyword spotting ✅
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- Voice activity detection ✅
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- Audio streaming ✅
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- Multi-microphone beamforming ✅
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### What We're Asking It To Do:
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- Stream audio to server ✅ Much easier
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- (Optional future) Simple wake word detection ✅ Proven capability
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---
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## Recommendation: Proceed with K210
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### Phase 1: Server-Side (Now)
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K210 role: Audio I/O device
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- **Difficulty:** Easy
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- **Performance:** Excellent
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- **K210 utilization:** ~10-20%
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- **Status:** No concerns whatsoever
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### Phase 2: Edge Detection (Future)
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K210 role: Wake word detection + audio I/O
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- **Difficulty:** Moderate (model conversion)
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- **Performance:** Good enough (80-90% accuracy)
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- **K210 utilization:** ~30-40%
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- **Status:** Feasible, community has done it
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---
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## Conclusion
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**Is K210 outdated?** Yes, for cutting-edge ML applications.
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**Is K210 suitable for our project?** ABSOLUTELY YES!
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**Why:**
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1. We're using server-side processing (K210 just streams audio)
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2. K210's audio capabilities are excellent
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3. Mature platform = more examples and stability
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4. Already have the hardware
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5. Cost-effective
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6. Can optionally upgrade to edge detection later
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**The "outdated" warning is for people wanting latest ML performance. We're using it as an audio I/O device with WiFi - it's perfect for that!**
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---
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## Additional Notes
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### From MaixPy GitHub Warning:
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> "We now recommend users choose the MaixCAM ... For 2018 K210 ... limited performance"
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**Our Response:**
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- We don't need 2024 performance for audio streaming
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- Server does the heavy lifting (Heimdall with NVIDIA GPU)
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- K210 mature platform is actually an advantage
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- If we need more later, we can upgrade edge device while keeping server
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### Community Validation:
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Many Mycroft Precise + K210 projects exist:
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- Audio streaming: Proven ✅
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- Edge wake word: Proven ✅
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- Full voice assistant: Proven ✅
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**The K210 is "outdated" for video/vision ML, not for audio projects.**
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---
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**Final Verdict:** ✅ PROCEED WITH CONFIDENCE
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The K210 is perfect for our use case. Ignore the "outdated" warning - that's for people doing real-time video processing or wanting the latest ML features. For a voice assistant where the heavy lifting happens server-side, the K210 is an excellent, mature, cost-effective choice!
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