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TensorFlow Lite - MicroSpeech

TensorFlow Lite is an open-source deep learning framework for on-device interference.

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TensorFlow Lite is an open-source, product ready, cross platform deep learning framework that converts a pre-trained model in TensorFlow to a special format that can be optimised for speed or storage. In this example, it will captured audio with a microphone to detect the words "yes" or "no".

Ameba RTL8722DM_MINI is a low-power dual-band WLAN and Bluetooth Low Energy SoC by Realtek. The RTL8722DM_MINI also include memory for Wi-Fi protocol functions and application making it simple for anyone to develop various kind of IoT applications. At the same time it has a wide range of peripheral interfaces. With all these interfaces, it can connect to most of the electronics components like LEDs, temperature and humidity sensors, and so on.

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  • 1 × RTL8722DM_MINI Microcontroller
  • 2 × LED Fiber Optics / Emitters

  • 1
    Setup

    Connect the LEDs to the RTL8722DM_MINI board as shown in the following wiring diagram.

    Download the Ameba customized version of TensorFlow Lite for Microcontrollers Library at:

    https://github.com/ambiot/ambd_arduino/tree/master/Arduino_zip_libraries. 

    Follow the instructions at  https://www.arduino.cc/en/guide/libraries to install it.

    Ensure that the patch files found at  https://github.com/ambiot/ambd_arduino/tree/master/Ameba_misc/  are also installed.

  • 2
    Programming

    To open the example code, Go to "Files"→ "Examples" → "TensorFlowLite_Ameba" → "micro_speech"

  • 3
    Final Results

    Upload the code and press the reset button on the Ameba board once the upload has completed.

    Once it is running, you should see the yellow led flashing, which indicates that it is processing the audio. Saying the word "yes" will cause the green led on the board to light up. "no" will cause the red LEd to light up. If the word is not recognised, the blue LED on the board will light up.

    The result will be output to the Serial Monitor, which appears like the following picture.

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