10-10-2012, 05:12 PM
Emotional Annotation of Text
Emotional Annotation of Text.pdf (Size: 983.3 KB / Downloads: 156)
INTRODUCTION
Emotional annotation of text is a step towards implementing affective computing. Affective Computing is computing that relates to, arises from, or deliberately influences emotion and other affective phenomena. The field was originally named and defined treating affect and emotion essentially synonymously and there is still no widely agreed upon definition of either the term "emotion" or "affect" in the literature; however, there is a general acceptance that affect is the broader term, and that states such as "interest ―are affects, whether or not they are emotions, while states such as "anger" are both an emotion and an affect. Regardless of the resolution of the precise definitions of emotion and affect, research in Affective Computing addresses the broader sense of the two terms, and contributes to Artificial Intelligence, Pattern Recognition, Machine Learning, Human-Computer Interaction, Social Robotics, Autonomous Agents, Cognitive and Affective Sciences, Affective Neuroscience, Neuroeconomics, Health-behavior Change, and many other areas where technology is used to detect, recognize, measure, model, simulate, communicate, elicit, handle, or otherwise understand and directly influence emotion and other affective phenomenon.
Imagine your robot entering the kitchen as you prepare breakfast for guests. The robot looks happy to see you and greets you with a cheery "Good morning." You mumble something it does not understand. It notices your face, vocal tone, smoke above the stove, and your slamming of a pot into the sink, and infers that you do not appear to be having a good morning. Immediately, it adjusts its internal state to ―subdued," which has the effect of lowering its vocal pitch and amplitude settings, eliminating cheery behavioral displays, and suppressing unnecessary conversation. Suppose you exclaim unprintable curses that are out of character for you, yank your hand from the hot stove, rush to run your fingers under cold water, and mutter "... ruined the sauce." While the robot's speech recognition may not have high confidence that it accurately recognized all of your words, its assessment of your affect and actions indicates a high probability that you are upset and
possibly hurt. At this moment it might turn its head with a look of concern, search its empathetic phrases and select, "Burn-Ouch ... Are you OK?" and wait to see if you are, before selecting the semantically closest helpful response, "Shall I list sauce recipes?" As it goes about its work helping you, it watches for signs of your affective state changing - positive or negative. It may modify an internal model of you, representing what is likely to elicit displays such as pleasure or displeasure from you, and it may later try to generalize this model to other people, and to development of common sense about people's affective states. It looks for things it does that are associated with improvements in the positive nature of your state, as well as things that might frustrate or annoy you. As it finds these, it also updates its own internal learning system, indicating which of its behaviors you prefer, so it becomes more effective in how it works with you.
This seminar deals with the various technologies behind annotation of text. Given a text how to get the emotion corresponding to that text?. The way in which the meaning of a sentence is built from the meaning of its words has been a subject of study in computational linguistics for a long time. No such study has been carried out for the way in which the emotional connotations of a sentence are affected by the emotional connotations of its words. Existing approaches to this task rely most often on a simplified representation of the sentence as a bag of words, where all words contribute in equal measure, much in the way information retrieval simplifies the treatment of text. However, intuitively certain words can probably be considered more significant, depending on the role they play in the word from their syntactic or semantic structure. An important hypothesis is that if this kind of sentence structure were to be represented computationally in a way that modeled how the emotional contributions of words affect the emotional connotations of the sentence, it would provide the means for capturing these intuitions. A static ontology of word dependencies within a sentence fulfills the requirements for such a representation.
PROBLEM DOMAIN AND THE TECHNOLOGIES
Four basic topics are coming under problem domain and technologies: the computational representation of emotions, the Semantic Web technologies that have been employed, the natural language processing technique employed to obtain the syntactic structure of sentences (dependency analysis) and the review of the system chosen as domain of application.
computational representations of emotions
Emotions are not easy to define, because there are a lot of factors that contribute to them. A good definition of emotion must take into consideration: conscious feeling of emotion, process which takes place in the nervous system and in the brain and expressive models of emotion. Emotions take place when something unexpected happens and the so-called ―emotional effects‖ begin to take control.
Classification of emotions
Many of the terms used to describe emotions and their effects are difficult to tell apart from one another, as they are usually not well defined. This is due to the fact that the abstract concepts and the feelings associated with such concepts are very difficult to express with words. For this reason, there are a lot of methods for describing the characteristics of emotions: emotional categories and emotional dimensions which represent the essential aspects of emotional concepts.
Structure of emotions
There are several approaches in the literature for determining which are the basic emotions, or which emotions are more general than others. There is a general agreement that some full-blown emotions are more basic than others. The number of basic emotions is usually small. Some emotion categories have been proposed as more fundamental than others on the grounds that they include the others.