AI-Based Solutions for Enhancing In-Car Voice Assistants

Abstract

In-car voice assistants have gained immense popularity in the automotive industry. These digital companions play a key role in customer comfort and partial automation and therefore are in close focus for the automotive industry and suppliers. Hence, the penetration rate of in-car voice assistants is predicted to gradually increase worldwide from the current over 40% to more than 60% in the year 2028. Despite this popularity, there are various reasons and justifications to further invest in research and development into this issue, such as improving the user interface with the combination of impressive voice interaction systems, augmented by AI technologies, increasing safety by mitigating driver distraction and muscle pain, or leveraging new business and usage models through a new service portfolio, including multimodal interaction and data monetization models, to enable all segments of society to use vehicles regardless of age or impairments. Hence, the paper aims to explore these critical issues and offer novel benefits of integrating new AI technologies and models, targeting to provide flexible and more natural user interfaces and to possibly enhance the setting in multimodal voice interaction. Therefore, the objective of this paper is twofold: First, we provide a comprehensive overview of current work, especially concerning in-car voice applications as conversational user interfaces, focusing on the parked drive use case and discussing some existing issues and limitations of the studies, which can compel industry practitioners and academics to seek new approaches and future studies. Second, the paper discusses in detail some AI solutions that have benefited in recent periods from the shift of new capabilities in such technologies, such as new breakthrough language models, enabling elastic data treatment and new loss applications, which can provide a fresh view on futuristic applications. Technically, we tackle several challenges such as the modes of voice assistant use, task complexity, and voice sound individuality via presented solutions in the paper. All these aims and the adoption of advanced functionalities enable the presented voice system to go beyond the mere voice interface, utilizing current evolutions and developments in new AI technologies, pertaining to adaptive losses and models. Given the above, we think that the degree of innovativeness is high as a result of the new technological advancements that are utilized, and the extent to which the solution is pushed towards the leading edge of technology, and the combination of different measures that are being adapted, namely, recent achievements and novelizations are coupled for maximum innovation in the field. Certainly, the system has the capability to enhance the voice driving experience, providing more natural in-car voice-assisted solutions, with flexible and more conversational interactions.