Introduction

Welcome to my weekly report documenting my journey during Google Summer of Code 2023 with the Linux Foundation! In this project, I am working on enhancing the existing speech-to-text feature of Automotive Grade Linux (AGL) by introducing a Natural Language Intent engine and implementing software daemons/controllers to execute the extracted intent. This endeavor aims to significantly improve the user experience and functionality of the speech-to-text feature in automotive environments. Throughout this report, I will share my progress, challenges faced, and achievements made as I contribute to the development of AGL and pave the way for more intuitive and intelligent voice interactions in automobiles.

Summary of the week

During this week, I made significant progress in my GSoC project. I successfully completed several yocto AGL recipes, expanding the existing lapack recipe and creating new recipes for python3-threadpoolctl, python3-joblib, python3-num2words, and python3-pyaml. These recipes were created successfully without any major issues. However, I did encounter some challenges while working on the recipes for Scipy and Scikit-Learn.

Tasks completed

I developed following Yocto AGL recipes successfully this week:

• Created a recipe for python3-threadpoolctl.
• Created a recipe for python3-joblib.
• Created a recipe for python3-num2words.
• Created a recipe for python3-pyaml.
• Extended the existing lapack recipe to incorporate additional functionality.

The recipes have been incorporated into the existing meta-offline-voice-agent, a copy of which can be found here.

Tasks leftover

The following tasks were leftover this week:

• The SciPy recipe errors need to be resolved.
• After building of SciPy, Scikit-Learn needs to be built.

Next steps

In the upcoming week, I have outlined the following tasks that I will be focusing on:

• Resolve SciPy recipe errors: During the creation of the Scipy recipe, I encountered RPATH errors during the quality assurance (QA) checks. My next step is to investigate and address these errors to ensure a successful recipe for Scipy. An example of the encountered error is as follows:

  ERROR: python3-scipy-1.5.4-r0 do_package_qa: QA Issue: package python3-scipy contains bad RPATH /home/malik/AGL/build-master/tmp/work/corei7-64-agl-linux/python3-scipy/1.5.4-r0/recipe-sysroot/usr/lib in file /home/malik/AGL/build-master/tmp/work/corei7-64-agl-linux/python3-scipy/1.5.4-r0/packages-split/python3-scipy/usr/lib/python3.10/site-packages/scipy/sparse/linalg/eigen/arpack/_arpack.cpython-310-x86_64-linux-gnu.so
  ... and so on
  

• Complete the remaining rust-based recipes: Apart from the Scipy recipe, there are other two rust-based recipes that need to be developed. I will prioritize completing these remaining recipes, ensuring their successful integration into the yocto AGL environment.

Conclusion

Overall, this week was productive, and I am satisfied with the progress made in achieving the goals outlined for the week. I am excited to continue my GSoC journey and further enhance the speech-to-text feature in Automotive Grade Linux.

Resources

The following resources were utilized during the week:

• Yocto - Writing a new recipe
• Building your own recipes from first principles