Industry 2 (Presentations abstract) - Olympics on the Google Assistant: Modular Conversation Design
Creators: name: Pham, Ryan
Publisher: name: figshare
Year: 2022
Subjects: subject: 190205 Interactive Media
subject: FOS: Arts (arts, history of arts, performing arts, music)

description: ABSTRACT With the development of automotive industry and transport infrastructure, the number of drivers continues to grow rapidly, and fatigue driving becomes increasingly prominent as one of the major factors causing traffic accidents. Relevant researches show that many traffic accidents can be effectively avoided if the fatigue state of the drivers is monitored in real-time and corresponding alerts are issued in the early period of fatigue driving. At present, driving fatigue state has been recognized through diverse technologies, with the main detection methods based on driving operation data, facial data, or physiological data. The detection method based on driving operation data is the most traditional method, and is easy to implement. Nevertheless, due to the influences of road conditions, operation habits and climate conditions, the accuracy is relatively low. With the rise of computer vision technology, the method based on facial data is gradually applied to identify driving fatigue state. However, the method can only detect the fatigue state until it is obvious, and cannot predict it at the early stage. Moreover, the accuracy is greatly affected by ambient light and drivers’ sitting postures. The detection method based on physiological signals may be the best choice, but, there are only technological fruits applicable to lab environment instead of products that meet industrial standards in the market so far. This paper will introduce the global first intelligent driving fatigue detection system (IDFDS) based on advanced bio-sensing and physiological computing technology. With an intelligent ring, a mobile app and a management system, the IDFDS can be customized for different industries. It has been an important part of the central control system of car makers so far, and is expected to be tested and accepted by car makers in July 2020, and to hit the market in September 2020. Besides, the IDFDS can also be provided to the investigators who are interested in fatigue driving as an experimental research platform. While many voice assistants use natural language processing and understanding to determine a user’s intent, Conversation Designers (CxDs) create many responses by producing voice user interface specs. These are often bespoke solutions, optimized for a feature. However, this approach is difficult to scale. This industry talk describes the design process of the first Olympics experience on Google Assistant and how it uses modular design to scalably answer millions of questions. To do this effactively, the design process required grouping together frequently asked queries, creating modular design components based on available data, and emphasizing/de-emphasizing components of an answer to get the widest intent coverage. <br> <strong>HOW TO CITE (APA)</strong> Pham, R. (2022). Olympics on the Google Assistant: Modular Conversation Design [Presentation abstract]. In <em>Industry Talks &amp; Exhibitions - ACM International Conference on Interactive Media Experiences: IMX 2022</em> (pp. 47). Aveiro, Portugal.