Abstract: Virtual Assistants (VAs) are widely used in many fields. Recently, VAs have been effectively applied in technical drawing tasks, such as in Photoshop and Microsoft Word. Understanding multi-intent commands in VAs poses a significant challenge, especially when the language in query is low-resource, like Vietnamese (no training dataset available for technical drawing domain), which features complex grammar and a limited domain of usage. In this work, we proposing a three-step process to develop a voice assistant capable of understanding multi-intent commands in VAs for low-resource languages, particularly in responding to the SCADA Framework (SF) for performing drawing tasks: (1) for the training dataset, we developed a semi-automatic method for building a labeled command corpus; applying this method to Vietnamese, we built a corpus that includes 3,240 labeled commands; (2) for the multi-intent command processing phase, we introduced a method for splitting multi-intent commands into single-intent commands to enable VAs to perform them more efficiently. By experimenting with the proposed method in Vietnamese, we developed a VA that supports drawing on SF with an accuracy of over 96%. With the results of this study, we can completely apply them to SCADA system products to support the automatic control of techinical drawing operations in them as VAs.

Van-Vinh Nguyen, Ha Nguyen-Tien, Anh-Quan Nguyen-Duc, Trung-Kien Vu, Cong Pham-Chi and Minh-Hieu Pham, “Recognizing Multi-Intent Commands of the Virtual Assistant with Low-Resource Languages” International Journal of Advanced Computer Science and Applications(IJACSA), 15(11), 2024. http://dx.doi.org/10.14569/IJACSA.2024.01511125

@article{Nguyen2024,
title = {Recognizing Multi-Intent Commands of the Virtual Assistant with Low-Resource Languages},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.01511125},
url = {http://dx.doi.org/10.14569/IJACSA.2024.01511125},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {11},
author = {Van-Vinh Nguyen and Ha Nguyen-Tien and Anh-Quan Nguyen-Duc and Trung-Kien Vu and Cong Pham-Chi and Minh-Hieu Pham}
}