Before revision: Sentiment Analysis and Emotion Detection in conversation is key in a number of real-world applications, with different applications leveraging different kinds of data to be able to achieve reasonably accurate predictions. Multimodal Emotion Detection and Sentiment Analysis can be particularly useful  as applications will be able to use specific subsets of the available modalities, as per their available data, to be able to produce relevant predictions . Current systems dealing with Multimodal functionality fail to leverage and capture  the context of the conversation through all modalities, the current speaker and listener(s)
After revision: Sentiment Analysis and Emotion Detection in conversation is key in a number of real-world applications, with an increase in modalities available aiding a better understanding of the underlying emotions. Multi-modal Emotion Detection and Sentiment Analysis can be particularly useful as applications will be able to use specific subsets of the available modalities, as per their available data, to be able to produce relevant predictions . Current systems dealing with Multimodal functionality fail to leverage and capture the context of the conversation through all modalities, the current speaker and listener(s)