  The digital realm has witnessed the rise of various search modalities, among
which the Image-Based Conversational Search System stands out. This research
delves into the design, implementation, and evaluation of this specific system,
juxtaposing it against its text-based and mixed counterparts. A diverse
participant cohort ensures a broad evaluation spectrum. Advanced tools
facilitate emotion analysis, capturing user sentiments during interactions,
while structured feedback sessions offer qualitative insights. Results indicate
that while the text-based system minimizes user confusion, the image-based
system presents challenges in direct information interpretation. However, the
mixed system achieves the highest engagement, suggesting an optimal blend of
visual and textual information. Notably, the potential of these systems,
especially the image-based modality, to assist individuals with intellectual
disabilities is highlighted. The study concludes that the Image-Based
Conversational Search System, though challenging in some aspects, holds
promise, especially when integrated into a mixed system, offering both clarity
and engagement.
