Multimodal Dialogue Systems in the Era of Artificial Intelligence-Assisted Industry
Varini Awasthi, Rajat Verma, Namrata Dhanda · 2024
The primary objective of this chapter is to lay out an in-depth study and evaluation of multimodal dialogue systems, taking into consideration their capabilities, difficulties, and prospective implementations. A multimodal dialogue system is an ensemble of sophisticated conversational Artificial Intelligence (AI) frameworks combining a wide range of modalities, involving text, audio, images, gestures, and other kinds of input and output, to promote instinctive and natural interactions between humans and machines. These platforms strive to replicate human-like discussions by incorporating multiple types of regular interactions in real-life scenarios. This chapter sets out to circumvent the inherent limitations of the existing technologies and look for innovative approaches, while highlighting and fixing the drawbacks in the present structures through an extensive review. It engages in a profound analysis of the architecture and operation of multimodal dialogue systems. It also aims to look into discourse control, modality integration, and context understanding techniques. It aspires to build cutting-edge frameworks and methods for effective modalities fusion, dialogue control, and context modeling. Additionally, it wants to look at real-world applications in industries like retail, travel, and customer service, stressing the benefits and value of multimodal dialogue systems. The primary objective is to improve human–machine interactions by helping to develop more dependable, context-aware, and lifelike systems .