The ESP-SR Solution for AI Assistants

Build Differentiated Voice Products with On-Device AI, Zero Cloud Dependency & 50% Faster Time-to-Market

Why ESP-SR? The Edge Voice Revolution

Traditional voice assistants rely on cloud processing, creating latency, privacy risks, and recurring costs. ESP-SR (Espressif Speech Recognition) disrupts this model by delivering full-stack voice intelligence directly on ESP32 chips—enabling real-time wake-word detection, command recognition, and acoustic processing without cloud dependency. For OEMs building smart speakers, industrial controllers, or consumer gadgets, it slashes BOM costs by 30% while ensuring GDPR-compliant privacy.

I. The ESP-SR Stack: Beyond Basic Voice Control

🎤 1. Acoustic Front-End (AFE)

Hardware-optimized algorithms for studio-grade audio preprocessing:

• AEC (Echo Cancellation): Eliminates speaker feedback in real-time.

• BSS (Blind Source Separation): Isolates target speech from multi-directional noise using dual mics.

• NS (Noise Suppression): Removes background interference (e.g., factory machinery).

• VAD (Voice Activity Detection): Reduces CPU load by filtering non-speech audio.

🔔 2. WakeNet: Ultra-Low Power Wake-Word Engine

• Runs at <5% CPU utilization on ESP32-S3, enabling years of battery life.

• Supports custom wake words (e.g., brand-specific phrases) with 95% detection accuracy.

• Pre-trained models for “Alexa,” “Hi, ESP,” and “Hi, Lexin”.

🗣️ 3. MultiNet: Offline Command Recognition

• Recognizes 200+ customizable commands in English/Chinese (e.g., “Turn on lights,” “Set temperature to 25°C”).

• Dynamic phrase binding—no retraining needed for new commands.

⚡ 4. Edge AI Acceleration

• Leverages ESP32-S3’s NPU for <100ms latency—6.25x faster than vanilla ESP32.

• Supports multi-mic arrays (1–4 channels) with flexible spacing for industrial designs.

II. Hardware Accelerators: From Prototyping to Production

1. ESP-EYE DevKit

• Core: ESP32-S3 with 8MB PSRAM + 4MB Flash

• Sensors: 2MP camera + dual digital mics

• Use Case: Voice-controlled security cams with face/voice fusion.

2. ESP32-S3-BOX-3

• Display: 2.4″ touchscreen (320×240) + capacitive UI

• AI Expansion: Optional radar/thermal sensors via PCIe connectors

• Generative AI Ready: Integrates ChatGPT/Baidu Wenxin for conversational agents.

3. ESP32-S3-Korvo-1

• Audio: 3-mic array + ES7210 ADC for far-field voice pickup (5m range).

• Certified: Amazon AVS-qualified for Alexa Built-in devices.

III. Real-World Applications: Voice Where It Matters

IV. Why OEMs/ODMs Choose ESP-SR

✅ Cost & Scalability

• Single-Chip Design: Eliminates external DSPs/CODECs—$1.80/unit at 100K volumes.

• Unified BOM: ESP32-S3 modules reduce assembly complexity by 25%.

✅ Certification & Compliance

• Pre-certified for FCC/CE/Alexa AVS.

• PSA Level 2 security (Secure Boot + AES-XTS encryption).

✅ Production-Ready Tools

• ESP-ZeroCode Platform: Drag-and-drop firmware configurator for voice commands.

• Custom Wake Word Service: Train brand-specific phrases in <2 weeks.

• 12-Year Long-Term Supply: Guaranteed component availability.

V. Getting Started: From Sample to Shipment

1. Prototype:

   • Order ESP-EYE or ESP32-S3-BOX-3.

   • Clone ESP-Skainet GitHub repo for sample code.

2. Develop:

   • Use ESP-IDF’s menuconfig to enable AFE/WakeNet/MultiNet.

   • Bind voice commands to GPIO/cloud actions in <20 LoC.

3. Scale:

   • Submit schematics for RF/EMC review.

   • Co-manage FCC/CE/Alexa certification.

*”ESP-SR cut our voice product development from 18 months to 6—and passed Alexa certification in 3 weeks.”*
— Smart Home OEM Partner, 2024

Launch Your Voice Product Line

For OEM/ODM Pricing, Custom SDKs, or Technical Consultations:
📧 sales@esp32s.com

*Empowering 10M+ voice devices globally • Supports ESP32-S3/P4/C6 • Rev 4.0*