Music expresses emotion. However, analyzing the emotion in music by computer is a difficult task. Some work can be found in the literature, but the results are not satisfactory. In this paper, an emotion detection and classification system for pop music is presented. The system extracts feature

technologies such as chat don’t capture people’s expressions or intonations, they fail to provide crucial emotional content. By modeling users’ real-time facial expressions using a 3D agent, the proposed system adds emotional content and maintains user privacy.

emotion regulation across the life span. Popular stereotypes suggest hat people become less emo-tional as they age: Out of the exuberance of abundant emotional energy in early adulthood evelops the moderation of cooler rationality in middle adulthood and older age (Bromley, 1990; Cumming & Henry, 1961

-dimensional mood vector for each day in the timeline. We compare our results to a record of popular events gathered from media and sources. We find that events in the social, political, cultural and economic sphere do have a significant, immediate and highly specific effect on the various dimensions of public mood

To what extent do all brains work alike during natural conditions? We explored this question by letting five subjects freely view half an hour of a popular movie while undergoing functional brain imaging. Applying an unbiased analysis in which spatiotemporal activity patterns in one brain were used

Emotion regulation has emerged as a popular topic, but there is doubt about its viability as a scientific construct. This article identifies conceptual and methodological challenges in this area of study and describes exemplar studies that provide a substantive basis for inferring emotion

We extend the concept of celebrity from the individual to the firm level of analysis and argue that the high level of public attention and the positive emotional responses that define celebrity increase the economic opportunities available to a firm. We develop a theoretical framework explaining

incorporating speaker independence and different room acoustics as needed in most reallife settings. This paper introduces the challenge, the corpus, the features, and benchmark results of two popular approaches towards emotion recognition from speech. Index Terms: emotion, challenge, feature types

, this work examines readers ’ emotional states. The first approach proposed in this paper minimizes pairwise ranking errors. In the second approach, regression is used to model emotional distributions. Experiment results show that the regression method is more effective at identifying the most popular

Abstract-Emotion is a useful mean to organize music library, and automatic music emotion recognition is drawing more and more attention. Music structure information is imported to improve the result for music emotion regression. Music dataset with emotion and structure annotations is built