CMU Multimodal Opinion Sentiment and Emotion Intensity (CMU-MOSEI) is the largest dataset of sentence level sentiment analysis and emotion recognition in online videos. CMU-MOSEI contains more than 65 hours of annotated video from more than 1000 speakers and 250 topics.
157 PAPERS • 3 BENCHMARKS
the YF-E6 emotion dataset using the 6 basic emotion type as keywords on social video-sharing websites including YouTube and Flickr, leading to a total of 3000 videos. The dataset is labeled through crowdsourcing by 10 different annotators (5 males and 5 females), whose age ranged from 22 to 45. Annotators were given detailed definition for each emotion before performing the task. Every video is manually labeled by all the annotators. A video is excluded from the final dataset when over half of annotations are inconsistent with the initial search keyword.
10 PAPERS • 1 BENCHMARK