On-Device Wake Word Detection - ESP32S3
Budget: ₹600 – ₹1,500 INR
I'm looking for a skilled developer to build a lightweight, real-time solution that continuously listens to audio input and triggers a response when the user says "hello". This model must run entirely on-device, optimized for the ESP32-S3 board.
Key Requirements:
- Proficient in Arduino programming (C/C++).
- Experience with ESP32-S3, especially with audio capture (I2S) and TensorFlow Lite Micro (TFLM).
- Experience in implementing wake word detection using:
- Pretrained Teachable Machine or similar models.
- Libraries like tflm_esp32, micro_speech, or alternatives.
Ideal Skills and Experience:
- Strong background in embedded systems.
- Familiarity with wake word detection algorithms.
- Ability to optimize models for low-power devices.
Key Requirements:
- Proficient in Arduino programming (C/C++).
- Experience with ESP32-S3, especially with audio capture (I2S) and TensorFlow Lite Micro (TFLM).
- Experience in implementing wake word detection using:
- Pretrained Teachable Machine or similar models.
- Libraries like tflm_esp32, micro_speech, or alternatives.
Ideal Skills and Experience:
- Strong background in embedded systems.
- Familiarity with wake word detection algorithms.
- Ability to optimize models for low-power devices.