Picovoice Shepherd - STM32H747

The STM32H747 discovery kit is a development board featuring a dual-core processor with Arm Cortex-M7 and Cortex-M4. It processor has 2MB of on-chip flash memory and 1MB of RAM. The Cortex-M7 core operates at up to 480 MHz. Picovoice uses Cortex-M7 core for voice recognition.

Picovoice Shepherd is the first no-code platform for building voice interfaces on microcontrollers. It enables creating voice experiences similar to Alexa that run entirely on microcontrollers. Picovoice Shepherd accelerates prototyping, mitigates technical risks, and shortens time to market. Paired with Picovoice Console users can deploy custom voice models into microcontrollers instantly.

Platforms

Linux (x86_64)
macOS (x86_64, arm64)
Windows (x86_64)

Requirements

Picovoice Account and AccessKey
Python 3
PIP
tkinter
STM32F469 discovery kit

Picovoice Account & AccessKey

Signup or Login to Picovoice Console to get your AccessKey. Make sure to keep your AccessKey secret.

Setup

Install Python 3.
- macOS: Install Python 3 through Homebrew.
- Windows: Refer to this link to add Python to PATH environmental variable.
Install the pvshepherd Python package using PIP:

pip3 install pvshepherd

Install tkinter:

For Debian based Linux distribution:

sudo apt-get install python3-tk

For Linux distribution with yum installer:

sudo yum install tkinter

For macOS:

brew install [email protected]{$PYTHON_VERSION}

For Windows:
- tkinter is installed by default.

Usage

Run the following command from the terminal:

pvshepherd

On Linux, Shepherd will ask for the root password only on the first launch.

Upload the Picovoice Firmware

First, connect the board to the computer using a MICRO-USB Type-B cable. STM32H747 discovery has three USB ports on it; Make sure that the USB port on the top left side of the board is used as shown in the figure below:

Select STM32H747I-DISCO and the language of your choice on the first page.

Selecting your board and press the upload button at the bottom right corner of the window

Press the Upload Firmware button and wait for the operation to complete. One complete, the LCD on the board updates.

If Shepherd has an issue with flashing the board, update the on-board ST-LINK firmware using STSW-LINK007

Upload The Default Models

Get an AccessKey and paste it to the AccessKey field. The unique universal identifier (UUID) of Microcontroller on the board is at the top. You need this UUID to create custom models using Picovoice Console. It is also displayed on the board's LCD. For now, let's continue with the default models. Upload the default voice models to the board by pressing Use Default Models.

Selecting your models and press the upload button at the bottom right corner of the window

Test the Default Models

The board is ready. It has started processing the audio input from the microphone in real-time. It writes to the Shepherd console and on-board LCD when the Picovoice engine detects utterances of the given wake word and follow-on voice commands. Say:

Picovoice, set the living room lights purple

Picovoice will detect the occurrence of the custom wake word (Picovoice), and then extracts the intent from the follow-on spoken command:

{
   "is_understood" : "true",
   "intent": "changeColor",
   "slots": {
     "location" : "living room",
     "color" : "purple"
   }
 }

showing the intent extracted from the command on the board lcd

The Show Context button opens a new window and lists all the available voice commands.

Monitoring the board activities and changing its parameters

The volume and CPU usage are on the top left. The inference sensitivity of the engines can be changed on the fly. The sensitivity parameter controls the tradeoff between the miss rate and false alarm. A higher sensitivity reduces the miss rate (false reject rate) at the cost of increased false alarm rate.

Audio Debugging

You can record and save the audio fed to the Picovoice from Shepherd. Go to the Audio debugging tab and click on the Record Audio button.

Saving audio recorded by the board for debugging

Create Custom Models

Go back to the Upload Model page and copy the UUID to the clipboard using the Copy button.
Go to Picovoice Console to create models for Porcupine wake word engine and Rhino Speech-to-Intent engine.
Select Arm Cortex-M as the platform when training the model.
Select STM32 as the board type and provide the UUID of the chipset on the board.

Upload the Custom Models

Download your custom voice model(s) from Picovoice Console.
Decompress the zip file. The model file is either .ppn for Porcupine wake word or .rhn for Rhino Speech-to-Intent.
Go to the Upload Model page and select the models.
Press the Upload button.

Demo Project

Additionally, there is a demo project on the Picovoice GitHub repository for the STM32H747 discovery board to ease integrating the designed voice interface into projects.