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 substantial progress in enhancing the capabilities of the existing GRPC server by successfully integrating Snips and RASA. Additionally, I extended the RASA and Snips models to incorporate volume control functionality, enhancing the versatility of the voice interaction system.

Tasks completed

I successfully completed the following tasks over the course of this week:

• Integrated both Snips and RASA seamlessly into the pre-existing GRPC server infrastructure. This integration lays the foundation for a unified and efficient voice interaction system.
• Enhanced the RASA and Snips models by introducing support for volume controls by adding the necessary intents and entities to the models.

Tasks leftover

No tasks were leftover this week.

Next steps

In the upcoming week, I have outlined the following tasks to be completed:

• Integrate Kuksa: I plan to integrate Kuksa into the existing GRPC server setup. This integration will enable the execution of intents through Kuksa, expanding the range of functionalities the voice interaction system can offer.

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

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