Natural Language Goal Understanding for Smart Home Environments
10th International Conference on the Internet of Things (IoT '20)
One of the main challenges of the Internet of Things (IoT) is to enable end-users without technical experience to use, control or monitor smart devices.
However, enabling end-users to interact with these smart devices in an intuitive and natural way becomes increasingly important as they become more pervasive in our homes, workplaces and public environments.
Voice-based interfaces are the emerging trend to provide a more natural human-device interaction in smart environments.
Such interfaces require Natural Language Understanding (NLU) approaches to identify the meaning of end-users' voice inputs.
Designing voice interfaces that are not limited to a small, fixed set of pre-defined commands is far from trivial.
Existing voice-based solutions in the smart home domain either restrict the end-users to follow a strict language pattern, do not support indirect goals, require a large training dataset, or need a voice assistant located in the cloud.
In this paper, we propose an approach for understanding end-users goals from voice inputs in smart homes.
Our approach alleviates the need for end-users to learn or remember concrete operations of the devices and specific words/pattern structures rather it enables them to control their smart homes based on the desired goals (effects).
We evaluate the approach through application to a collection of 253 goals from real end-users and report on quality metrics.
The results demonstrate that our solution provides a good accuracy, high precision and acceptable recall for understanding end-users goals in the smart home domain.
Noura, Mahda; Heil, Sebastian; Gaedke, Martin: Natural Language Goal Understanding for Smart Home Environments. 10th International Conference on the Internet of Things (IoT '20), 2020.