Given a short query with keyphrases about a research idea in 2018 in the domain of artificial intelligence, recommend the relevant datasets to validate the research idea from options provided. A short description of the datasets is also provided to help you.

Query: A multi-modal variational autoencoder for joint learning of image, text, and audio

Keyphrases: multi-modal learning image, text

Dataset description:
URMP: URMP (University of Rochester Multi-Modal Musical Performance) is a dataset for facilitating audio-visual analysis of musical performances. The dataset comprises 44 simple multi-instrument musical pieces assembled from coordinated but separately recorded performances of individual tracks.
CelebA: CelebFaces Attributes dataset contains 202,599 face images of the size 178×218 from 10,177 celebrities, each annotated with 40 binary labels indicating facial attributes like hair color, gender and age.
RecipeQA: RecipeQA is a dataset for multimodal comprehension of cooking recipes. It consists of over 36K question-answer pairs automatically generated from approximately 20K unique recipes with step-by-step instructions and images.
CelebA-HQ: The CelebA-HQ dataset is a high-quality version of CelebA that consists of 30,000 images at 1024×1024 resolution.

Options:- A: URMP  B: CelebA  C: RecipeQA  D: CelebA-HQ
CelebA