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Emotient was a startup company which applied emotion recognition to reading frowns, smiles, and other expressions on faces, namely artificial intelligence to predict "attitudes and actions based on facial expressions". [40] Apple bought Emotient in 2016 and uses emotion recognition technology to enhance the emotional intelligence of its ...
Sentiment analysis (also known as opinion mining or emotion AI) is the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information.
Emotion recognition in conversation (ERC) is a sub-field of emotion recognition, that focuses on mining human emotions from conversations or dialogues having two or more interlocutors. [1] The datasets in this field are usually derived from social platforms that allow free and plenty of samples, often containing multimodal data (i.e., some ...
Recognizing emotional information requires the extraction of meaningful patterns from the gathered data. This is done using machine learning techniques that process different modalities, such as speech recognition, natural language processing, or facial expression detection. The goal of most of these techniques is to produce labels that would ...
Deep learning is a subset of machine learning that focuses on utilizing neural networks to perform tasks such as classification, regression, and representation learning.The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" them to process data.
AlphaFold is a deep learning based system developed by DeepMind for prediction of protein structure. [76] Otter.ai is a speech-to-text synthesis and summary platform, which allows users to record online meetings as text. It additionally creates live captions during meetings.
In January 2021, Uniphore acquired Emotion Research Lab, [25] a startup based in Spain that uses artificial intelligence and machine learning to analyze video and interpret emotions. [ 26 ] [ 27 ] The company received $140 million in Series D funding, led by Sorenson Capital Partners, in March 2021, bringing total funding to $210 million.
Multimodal learning is a type of deep learning that integrates and processes multiple types of data, referred to as modalities, such as text, audio, images, or video.This integration allows for a more holistic understanding of complex data, improving model performance in tasks like visual question answering, cross-modal retrieval, [1] text-to-image generation, [2] aesthetic ranking, [3] and ...