  We introduce MMIS, a novel dataset designed to advance MultiModal Interior
Scene generation and recognition. MMIS consists of nearly 160,000 images. Each
image within the dataset is accompanied by its corresponding textual
description and an audio recording of that description, providing rich and
diverse sources of information for scene generation and recognition. MMIS
encompasses a wide range of interior spaces, capturing various styles, layouts,
and furnishings. To construct this dataset, we employed careful processes
involving the collection of images, the generation of textual descriptions, and
corresponding speech annotations. The presented dataset contributes to research
in multi-modal representation learning tasks such as image generation,
retrieval, captioning, and classification.
