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Micro Speech Example

The Micro speech program analyzes an audio input with a voice recognition model that can detect 2 keywords - yes and no. The recognized keywords are then printed into a serial interface. The voice recognition model is implemented using TensorFlow Lite for Microcontrollers.

GitHub repository contains an implementation supporting Arm Virtual Hardware (AVH) CPUs as well as real hardware boards.

Micro speech demonstrates how to use the processor and peripheral abstraction layers for simpler software portability across different targets. The example repository contains documentation with running instructions.

Getting Started with Micro speech on Arm Virtual Hardware

Table of contents

  1. Prerequisites
  2. Accessing and launching the AMI
  3. Import and build example
  4. Automated CI/CD with GitHub Actions
  5. To go further

1. Prerequisites

2. Accessing and launching the AMI

2.1. Find AMI on AWS Marketplace

  1. Log into your AWS account and select AWS Marketplace Subscriptions service
  2. Go to Discover products and search for Arm Virtual Hardware (with spaces)
AWS AMI subscription button
  1. Click on Continue to subscribe to the AMI > Continue to configuration > Continue to launch
  2. Choose c5.large instance type. This type has 2 powerful vCPU and 4 GB of RAM which is enough resources to run the AMI and simulation fast.
AWS instance size list
  1. If you don't have a VPC (Virtual Private Cloud network) already, click on Create a VPC in EC2 * in the corresponding section. In the *Your VPCs interface, click on Actions > Create default VPC in the top-right corner.
AWS instance size list
  1. If you don't have a Security Group already, click on Create new security group based on seller settings in the corresponding section. This will allow SSH connection to the instance. Add a name and description to save it.
AWS instance size list
  1. If you don't have a Key Pair already, click on "Create a key pair in EC2" in the corresponding section. A SSH key pair correspond to a public key that will be copied on the server side (the running AVH AMI instance) and a private key needed by a client to connect to it (your local machine). In the Key pairs interface, click on Create a pair in the top-right corner and follow the default steps to download the private key that you will need to connect.
AWS key pair selection menu
  1. Click on Launch. You will see a "Congratulations" message to inform you that the instance was successfully deployed. Click on the link provided "You can view this instance on EC2 Console" to check the instance status and retrieve its Public IPv4 address.

2.2. (Alternative) Launch the AMI from AWS EC2

  1. Log into your AWS account and select Elastic Compute Cloud (EC2) service
  2. Locate Images > AMIs in the sidebar
  3. Search Public Images for ArmVirtualHardware (without spaces) and click on Launch.
AWS key pair selection menu
  1. Follow the steps with the default options. If this has not been configured already, you will need to create a VPC, a new security group similar to what is described in section 2.4.
  2. Click on Review and launch > Launch to select or create a key pair (see section 2.4). You will see a message to inform you that the instance was successfully launched. Click on the View instances link provided to check its status and retrieve its Public IPv4 address.

2.3. Enable AMI console

To connect to the running instance, you will need its Public IPv4 address. If you don't have it already, you can get from the EC2 > Instances.

Use SSH command on Linux, MacOS or Windows Powershell:

    ssh -i <key.pem> ubuntu@<AMI_IP_addr>

Or, if using MobaXterm on Windows:

  • Add new SSH session
  • Specify <AMI_IP_addr> as Remote host
  • Specify ubuntu as username
  • Enable Use private key and specify path to <key.pem>
MobaXterm SSH configuration

Or, if using PuTTY:

  • Use PuTTYgen to convert the .pem file to .ppk
  • Specify ubuntu@<AMI_IP_addr> in Session > Host name
PuTTY username and hostname/IP configuration
  • Specify path to key.pem in Session > Connection > SSH > Auth > Private key file for authentication
PuTTY private key configuration

2.4. [Optional] Enable <a href="" >Code Server</a> (Visual Studio Code)

The Arm Virtual Hardware AMI comes with an IDE (Visual Studio Code) which can be accessed with a web browser. To access it, you will need to:

  1. Start a SSH tunnel to the instance and forward port 8080. On Linux, MacOS or Windows Powershell:

    ssh -i <key.pem> -N -L 8080:localhost:8080 ubuntu@<AMI_IP_addr>

    The -N option holds the SSH tunnel connection and does not allow to execute other remote commands. This is useful for just forwarding ports.

    Or, with MobaXterm on Windows:

    • Add new SSH tunnel
    • Specify 8080 in My computer > Forwarded port
    • Specify <AMI_IP_addr> in SSH server
    • Specify ubuntu in SSH login
    • Specify 22 in SSH port
    • Specify localhost in Remote server
    • Specify 8080 in Remote port
    • Save configuration. Click on the key icon to specify the path to <key.pem>
    • Start the tunnel connection
MobaXterm SSH tunnel configuration
  1. Launch a web browser on your local machine and open the following URL: http://localhost:8080

2.5. [Optional] Enable Virtual Network Computing (VNC)

VNC is a protocol to enable remote desktop. The instruction below will securely enable VNC through a SSH tunnel.

In the AMI terminal:

  1. Enable VNC password (no need to enter a view-only password)


  2. Start the VNC server for the session

    sudo systemctl start vncserver@1.service

    To restart the VNC server after reboot

    sudo systemctl enable vncserver@1.service

On your local machine:

  1. Forward port 5901 on local machine​. On Linux, MacOS or Windows Powershell:

    ssh -I <key.pem> -N –L 5901:localhost:5901 ubuntu@<AMI_IP_addr>​

    Then, connect VNC client (e.g. Remmina, TigerVNC) to port 5901​. You will be prompted for password.

    Or, with MobaXterm on Windows:

    • Add new VNC session
    • Specify localhost as Remote hostname
    • Specify 5901 as Port
    • Select the Network settings tab configure the SSH gateway with:
      • <AMI_IP_addr> as Gateway host
      • ubuntu as Username
      • 22 as Port
      • Enable Use SSH key and specify path to <key.pem>
MobaXterm VNC configuration through SSH gateway

3. Import and build example

3.1. Fork and clone example

  1. Open a web browser and enter the following URL:
  2. Log in to your github account and click on Fork (upper right)
  3. In the AMI terminal:
     git config --global YourGitHubName​
     git config --global​
     git config --list​
     git clone<YourGitHubName>/AVH-TFLmicrospeech

3.2. Build example within the AMI

In the AMI terminal:

  1. Navigate to build folder​

    cd AVH-TFLmicrospeech/Platform_FVP_Corstone_SSE-300_Ethos-U55​

  2. Use cp_install utility (do once) to install the necessary CMSIS Packs​ dependencies packlist​

  3. Use (cbuild)[] to build the software project​ (this should take about a minute) microspeech.Example.cprj

3.3. Run the example in place

In the AMI terminal:

  1. Run script to load application to model and execute​


    This will run the application until it terminates (about a minute). You can terminate the simulation faster by specifying the number of cycles:

    ./ --cyclelimit 100000000
  2. Observe banner and output log​
     Fast Models [11.16.14 (Sep 29 2021)]​
     Copyright 2000-2021 ARM Limited.​
     All Rights Reserved.​
     telnetterminal0: Listening for serial connection on port 5000​
     telnetterminal1: Listening for serial connection on port 5001​
     telnetterminal2: Listening for serial connection on port 5002​
     telnetterminal5: Listening for serial connection on port 5003​
     Ethos-U rev afc78a99 --- Aug 31 2021 22:30:42​
     (C) COPYRIGHT 2019-2021 Arm Limited​
     Heard yes (146) @1000ms
     Heard no (145) @5600ms
     Heard yes (143) @9100ms
     Heard no (145) @13600ms
     Heard yes (143) @17100ms
     Heard no (145) @21600ms
     Info: Simulation is stopping. Reason: Cycle limit has been exceeded.
     Info: /OSCI/SystemC: Simulation stopped by user.
     [warning ][main@0][01 ns] Simulation stopped by user
     --- cpu_core statistics: ------------------------------------------------------
     Simulated time                          : 23.999999s
     User time                               : 25.804117s
     System time                             : 3.336213s
     Wall time                               : 29.132544s
     Performance index                       : 0.82
     cpu_core.cpu0                           :  26.36 MIPS (   768000000 Inst)

3.4. Edit example

In the AMI terminal:

  1. Navigate to source folder​

    cd ../micro_speech/src/​

  2. Edit using the nano text editor for example:


    And change output (e.g. add your name as below)​

    TF_LITE_REPORT_ERROR(error_reporter, “YourName Heard %s (%d) @%dms", found_command, score, current_time);
  3. Save (Ctrl+X with nano), rebuild (cbuild will just rebuild the files that have changed) and run to verify change​
     cd ../../Platform_FVP_Corstone_SSE-300_Ethos-U55​ microspeech.Example.cprj​

3.5 Submit changes back to GitHub

In the AMI terminal

  1. mark changed file(s) you wish to submit​
     cd ../micro_speech/src/​
     git add .​
  2. Commit changes, with arbitrary message​
     git commit -m "Added my name to output message"
  3. Verify the repository referenced is your forked copy​
     git remote -v​
  4. Submit changes back to your repository​

     git push​

    You will be asked your login and Personal Access Token (password) information.

    To ​enable Personal Access Token in GitHub:

    • go to Settings > Developer settings > Personal access tokens > Generate new token
    • Enable repo to access the repository from the command-line
    • Generate and copy the token to provide

    In your own fork on Github, observe the change registered<YourGitHubName>/AVH-TFLmicrospeech​/blob/main/micro_speech/src/​

4. Automated CI/CD with GitHub Actions

4.1. Configure GitHub Actions

In your own fork on GitHub

  1. Navigate to Settings > Actions > Runners
  2. Add New self-hosted runner
GitHub New self-hosted runner button
  1. Select Linux, x64 Runner image and copy the commands to set up
GitHub Self-hosted runner configuration instructions

4.2. Setup runner on AMI

In the AMI terminal

  1. Go to base directory
     cd /home/ubuntu
  2. Copy the commands from GitHub to configure with default options (no need for a runner group name)
  3. Once configured, use to start the runner on the AMI
     Connected to GitHub
     yyyy-mm-dd hh:mm:ss: Listening for Jobs
    In Github, go the Runner tab to see the runner listed and idle
GitHub runner list

4.3. GitHub Actions workflow

  1. In Github, the file .github/workflows/virtual_hardware.yml defines the list of actions to perform (e.g. code checkout, build, run test script) on the runner and when (e.g. for every push to the repo)
  2. In a new AMI terminal, revert your change in and push to the repo
     cd AVH-TFLmicrospeech/micro_speech/src
     git add .
     git commit -m "Original message"
     git push
  3. Back to the first AMI terminal where the runner has been started with ./, the runner reports the status
     <timestamp>: Listening for Jobs
     <timestamp>: Running job: ci_demonstration
     <timestamp>: Job ci_demonstration completed with result: Succeeded
  4. In GitHub, locate the Actions sections and inspect the history of the workflow runs on the AMI instance
GitHub actions reports

4.4. Demonstration of a failed workflow

  1. Change the code to be non-valid C e.g. edit and remove the semicolon at the end of the line:
     TF_LITE_REPORT_ERROR(error_reporter, “YourName Heard %s (%d) @%dms", found_command, score, current_time)
  2. Commit change to GitHub
     git add .
     git commit -m "Example of failure"
     git push
  3. Observe in AMI that the runner reports failure
     <timestamp>: Running job: ci_demonstration
     <timestamp>: Job ci_demonstration completed with result: Failed
    Same in GitHub's Actions tab
GitHub actions reports

5. To go further

The Machine Learning Group at Arm have developed other examples which can be run in with the Arm Virtual Hardware AMI.

The instructions in the quick start guide are easily reproducible in the AMI. You will need to enable VNC to visualize.

For more information on Arm's solution for IoT:

Have questions, comments, or suggestions? Visit the Arm Virtual Hardware support forum