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: We explore a new approach to automatically generate questions from images that will aid in the development of a robust

Keyphrases: speech emotion recognition

Dataset description:
Image Paragraph Captioning: The Image Paragraph Captioning dataset allows researchers to benchmark their progress in generating paragraphs that tell a story about an image. The dataset contains 19,561 images from the Visual Genome dataset.
SQuAD: The Stanford Question Answering Dataset (SQuAD) is a collection of question-answer pairs derived from Wikipedia articles. In SQuAD, the correct answers of questions can be any sequence of tokens in the given text.
IEMOCAP: Multimodal Emotion Recognition IEMOCAP The IEMOCAP dataset consists of 151 videos of recorded dialogues, with 2 speakers per session for a total of 302 videos across the dataset. Each segment is annotated for the presence of 9 emotions (angry, excited, fear, sad, surprised, frustrated, happy, disappointed and neutral) as well as valence, arousal and dominance.
PieAPP dataset: The PieAPP dataset is a large-scale dataset used for training and testing perceptually-consistent image-error prediction algorithms. The dataset can be downloaded from:  server containing a zip file with all data (2.2GB) or Google Drive (ideal for quick browsing).

Options:- A: Image Paragraph Captioning  B: SQuAD  C: IEMOCAP  D: PieAPP dataset
IEMOCAP