Given a short query with keyphrases about a research idea in 2020 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 speech emotion recognition algorithm based on multi-feature and multi-lingual fusion.

Keyphrases: speech emotion recognition

Dataset description:
EXAMS: A new benchmark dataset for cross-lingual and multilingual question answering for high school examinations. Collects more than 24,000 high-quality high school exam questions in 16 languages, covering 8 language families and 24 school subjects from Natural Sciences and Social Sciences, among others.
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.
Drive&Act: The Drive&Act dataset is a state of the art multi modal benchmark for driver behavior recognition. The dataset includes 3D skeletons in addition to frame-wise hierarchical labels of 9.6 Million frames captured by 6 different views and 3 modalities (RGB, IR and depth).
SEN12MS-CR: SEN12MS-CR is a multi-modal and mono-temporal data set for cloud removal. It contains observations covering 175 globally distributed Regions of Interest recorded in one of four seasons throughout the year of 2018.

Options:- A: EXAMS  B: IEMOCAP  C: Drive&Act  D: SEN12MS-CR
IEMOCAP