News is an interesting application domain for “emotion sensing”, since readers often have a personal attitude or subjective opinion regarding certain events or entities reported about. Hence the ability to determine user-centric emotion on a given to

Several experiments have been carried out that revealed weaknesses of the current Text-To-Speech (TTS) systems in their emotional expressivity. Although some TTS systems allow XML-based representations of prosodic and/or phonetic variables, few publications considered, as a pre-processing stage, the use of intelligent text processing to detect affective information that can be used to tailor the parameters needed for emotional expressivity. This paper describes a technique for an automatic prosodic parameterization based on affective clues. This technique recognizes the affective information conveyed in a text and, accordingly to its emotional connotation, assigns appropriate pitch accents and other prosodic parameters by XML-tagging. This pre-processing assists the TTS system to generate synthesized speech that contains emotional clues. The experimental results are encouraging and suggest the possibility of suitable emotional expressivity in speech synthesis.

This paper describes a character-based system called "Emotion Sensitive News Agent" (ESNA). ESNA is been developed as a news aggregator to fetch news from different news sources chosen by a user, and to categorize the themes of the news into eight emotion types. A small user study indicates that the system is conceived as intelligent and interesting as an affective interface. ESNA exemplifies a recent research agenda that aims at recognizing affective information conveyed through texts. News is an interesting application domain where user may have marked attitudes to certain events or entities reported about. Different approaches have already been employed to "sense" emotion from text. The novelty of our approach is twofold: affective information conveyed through text is analyzed (1) by considering the cognitive and appraisal structure of emotions, and (2) by taking into account user preferences.

Studying the relationship between natural language and affective information as well as assessing the underpinned affective qualities of natural language are becoming crucial for improving human computer interaction. Different approaches have already been employed to "sense" affective information from text but none of those considered the cognitive structure of individual emotions and appraisal structure of those emotions adopted by emotion sensing programs. It has also been observed that previous attempts for textual affect sensing have categorized texts into a number of emotion groups, e.g. six so-called "basic" emotion proposed by Paul Ekman which we believe insufficient to classify textual emotions. Hence we propose a different approach to sense affective information from texts by applying the cognitive theory of emotions known as OCC model [1] which distinguishes several emotion types that can be identified by assessing valenced reactions to events, agents or objects described in the texts. In particular we want to create a formal model that can not only "understand" what emotions people wrap with their textual messages, but also can make automatic empathic response with respect to the emotional state detected in the text (e.g. in a chat system). We first briefly describe relevant works and then we explain our proposal with examples. Finally we conclude with future work plans.

Due to availability and accessibility of enormous Internet-based resources and dynamic nature of Web pages, the task of information retrieval is becoming more challenging and gradually tricky. This paper describes about agent based autonomous system, automatic report to presentation (ARP), with the notion of autonomous information service emerging as the result of integration among natural language processing, Web intelligence, and character-based agent interaction. The system, ARP, automatically builds a report on a topic or search phrase(s) given by a user by fetching a set of Web-pages; and then parsing; summarizing, affect-sensing and correlating information extracted from those. The system also makes a concise presentation automatically and, a group of character based software-agents autonomously present the topic in a story-telling manner employing text- to-speech engine with accompanied content-rich slides, different gestures and affects