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Emotion Recognition In Conversation
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. 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 combination of textual, visual, and acoustic data). Self- and inter-personal influences play critical role in identifying some basic emotions, such as, fear, anger, joy, surprise, etc. The more fine grained the emotion labels are the harder it is to detect the correct emotion. ERC poses a number of challenges, such as, conversational-context modeling, speaker-state modeling, presence of sarcasm in conversation, emotion shift across consecutive utterances of the same interlocutor. The task The task of ERC deals with detecting emotions expressed by the speakers in each utterance of the conversation. ERC depends on three primary factors – the conve ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Emotion Recognition
Emotion recognition is the process of identifying human emotion. People vary widely in their accuracy at recognizing the emotions of others. Use of technology to help people with emotion recognition is a relatively nascent research area. Generally, the technology works best if it uses multiple modalities in context. To date, the most work has been conducted on automating the recognition of facial expressions from video, spoken expressions from audio, written expressions from text, and physiology as measured by wearables. Human Humans show a great deal of variability in their abilities to recognize emotion. A key point to keep in mind when learning about automated emotion recognition is that there are several sources of "ground truth," or truth about what the real emotion is. Suppose we are trying to recognize the emotions of Alex. One source is "what would most people say that Alex is feeling?" In this case, the 'truth' may not correspond to what Alex feels, but may corre ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Emotion
Emotions are mental states brought on by neurophysiological changes, variously associated with thoughts, feelings, behavioral responses, and a degree of pleasure or displeasure. There is currently no scientific consensus on a definition. Emotions are often intertwined with mood, temperament, personality, disposition, or creativity. Research on emotion has increased over the past two decades with many fields contributing including psychology, medicine, history, sociology of emotions, and computer science. The numerous theories that attempt to explain the origin, function and other aspects of emotions have fostered more intense research on this topic. Current areas of research in the concept of emotion include the development of materials that stimulate and elicit emotion. In addition, PET scans and fMRI scans help study the affective picture processes in the brain. From a mechanistic perspective, emotions can be defined as "a positive or negative experience that is as ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dialogue
Dialogue (sometimes spelled dialog in American English) is a written or spoken conversational exchange between two or more people, and a literary and theatrical form that depicts such an exchange. As a philosophical or didactic device, it is chiefly associated in the West with the Socratic dialogue as developed by Plato, but antecedents are also found in other traditions including Indian literature. Etymology The term dialogue stems from the Greek διάλογος (''dialogos'', conversation); its roots are διά (''dia'': through) and λόγος (''logos'': speech, reason). The first extant author who uses the term is Plato, in whose works it is closely associated with the art of dialectic. Latin took over the word as ''dialogus''. As genre Antiquity and the Middle Ages Dialogue as a genre in the Middle East and Asia dates back to ancient works, such as Sumerian disputations preserved in copies from the late third millennium BC, Rigvedic dialogue hymns and the ''Mahab ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Interlocutor (linguistics)
In linguistics, discourse analysis, and related fields, an interlocutor is a person involved in a conversation or dialogue. Two or more people speaking to one another are each other's interlocutors. The terms ''conversation partner'', ''hearer'', or ''addressee'' are often used interchangeably with ''interlocutor''. According to Paul Grice, the behavior of interlocutors in ordinary conversation is governed by the cooperative principle. See also *Addressee honorific *Clusivity *Common ground (linguistics) *Conversation analysis *Discourse Discourse is a generalization of the notion of a conversation to any form of communication. Discourse is a major topic in social theory, with work spanning fields such as sociology, anthropology, continental philosophy, and discourse analysis. ... References Linguistics Pragmatics {{ling-stub ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Social Media
Social media are interactive media technologies that facilitate the creation and sharing of information, ideas, interests, and other forms of expression through virtual communities and networks. While challenges to the definition of ''social media'' arise due to the variety of stand-alone and built-in social media services currently available, there are some common features: # Social media are interactive Web 2.0 Internet-based applications. # User-generated content—such as text posts or comments, digital photos or videos, and data generated through all online interactions—is the lifeblood of social media. # Users create service-specific profiles for the website or app that are designed and maintained by the social media organization. # Social media helps the development of online social networks by connecting a user's profile with those of other individuals or groups. The term ''social'' in regard to media suggests that platforms are user-centric and enable communal ac ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Multimodal Sentiment Analysis
Multimodal sentiment analysis is a new dimension of the traditional text-based sentiment analysis, which goes beyond the analysis of texts, and includes other modalities such as audio and visual data. It can be bimodal, which includes different combinations of two modalities, or trimodal, which incorporates three modalities. With the extensive amount of social media data available online in different forms such as videos and images, the conventional text-based sentiment analysis has evolved into more complex models of multimodal sentiment analysis, which can be applied in the development of virtual assistants, analysis of YouTube movie reviews, analysis of news videos, and emotion recognition (sometimes known as emotion detection) such as depression monitoring, among others. Similar to the traditional sentiment analysis, one of the most basic task in multimodal sentiment analysis is sentiment classification, which classifies different sentiments into categories such as positive, n ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Fear
Fear is an intensely unpleasant emotion in response to perceiving or recognizing a danger or threat. Fear causes physiological changes that may produce behavioral reactions such as mounting an aggressive response or fleeing the threat. Fear in human beings may occur in response to a certain stimulus occurring in the present, or in anticipation or expectation of a future threat perceived as a risk to oneself. The fear response arises from the perception of danger leading to confrontation with or escape from/avoiding the threat (also known as the fight-or-flight response), which in extreme cases of fear (horror and terror) can be a freeze response or paralysis. In humans and other animals, fear is modulated by the process of cognition and learning. Thus, fear is judged as rational or appropriate and irrational or inappropriate. An irrational fear is called a phobia. Fear is closely related to the emotion anxiety, which occurs as the result of threats that are perceived to b ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Anger
Anger, also known as wrath or rage, is an intense emotional state involving a strong uncomfortable and non-cooperative response to a perceived provocation, hurt or threat. A person experiencing anger will often experience physical effects, such as increased heart rate, elevated blood pressure, and increased levels of adrenaline and noradrenaline. Some view anger as an emotion which triggers part of the fight or flight response. Anger becomes the predominant feeling behaviorally, cognitively, and physiologically when a person makes the conscious choice to take action to immediately stop the threatening behavior of another outside force. The English word originally comes from the term ''anger'' from the Old Norse language. Anger can have many physical and mental consequences. The external expression of anger can be found in facial expressions, body language, physiological responses, and at times public acts of aggression. Facial expressions can range from inward angling of the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Unsupervised Learning
Unsupervised learning is a type of algorithm that learns patterns from untagged data. The hope is that through mimicry, which is an important mode of learning in people, the machine is forced to build a concise representation of its world and then generate imaginative content from it. In contrast to supervised learning where data is tagged by an expert, e.g. tagged as a "ball" or "fish", unsupervised methods exhibit self-organization that captures patterns as probability densities or a combination of neural feature preferences encoded in the machine's weights and activations. The other levels in the supervision spectrum are reinforcement learning where the machine is given only a numerical performance score as guidance, and semi-supervised learning where a small portion of the data is tagged. Neural networks Tasks vs. methods Neural network tasks are often categorized as discriminative (recognition) or generative (imagination). Often but not always, discriminative tas ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Supervised Learning
Supervised learning (SL) is a machine learning paradigm for problems where the available data consists of labelled examples, meaning that each data point contains features (covariates) and an associated label. The goal of supervised learning algorithms is learning a function that maps feature vectors (inputs) to labels (output), based on example input-output pairs. It infers a function from ' consisting of a set of ''training examples''. In supervised learning, each example is a ''pair'' consisting of an input object (typically a vector) and a desired output value (also called the ''supervisory signal''). A supervised learning algorithm analyzes the training data and produces an inferred function, which can be used for mapping new examples. An optimal scenario will allow for the algorithm to correctly determine the class labels for unseen instances. This requires the learning algorithm to generalize from the training data to unseen situations in a "reasonable" way (see inductive b ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Recurrent Neural Network
A recurrent neural network (RNN) is a class of artificial neural networks where connections between nodes can create a cycle, allowing output from some nodes to affect subsequent input to the same nodes. This allows it to exhibit temporal dynamic behavior. Derived from feedforward neural networks, RNNs can use their internal state (memory) to process variable length sequences of inputs. This makes them applicable to tasks such as unsegmented, connected handwriting recognition or speech recognition. Recurrent neural networks are theoretically Turing complete and can run arbitrary programs to process arbitrary sequences of inputs. The term "recurrent neural network" is used to refer to the class of networks with an infinite impulse response, whereas "convolutional neural network" refers to the class of finite impulse response. Both classes of networks exhibit temporal dynamic behavior. A finite impulse recurrent network is a directed acyclic graph that can be unrolled and replace ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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