Disambiguating Music Emotion Using Software Agents
نویسندگان
چکیده
Annotating music poses a cognitive load on listeners and this potentially interferes with the emotions being reported. One solution is to let software agents learn to make the annotator’s task easier and more efficient. Emo is a music annotation prototype that combines inputs from both human and software agents to better study human listening. A compositional theory of musical meaning provides the overall heuristics for the annotation process, with the listener drawing upon different influences such as acoustics, lyrics and cultural metadata to focus on a specific musical mood. Software agents track the way these choices are made from the influences available. A functional theory of human emotion provides the basis for introducing necessary bias into the machine learning agents. Conflicting positive and negative emotions can be separated on the basis of their different function (reward-approach and threat-avoidance) or dysfunction (psychotic). Negative emotions have strong ambiguity and these are the focus of the experiment. The results of mining psychological features of lyrics are promising, recognisable in terms of common sense ideas of emotion and in terms of accuracy. Further ideas for deploying agents in this model of music annotation are presented.
منابع مشابه
Emotionface: Prototype Facial Expression Display of Emotion in Music
EmotionFace is a software interface for visually displaying the self-reported emotion expressed by music. Taken in reverse, it can be viewed as a facial expression whose auditory connection or exemplar is the time synchronized, associated music. The present instantiation of the software uses a simple schematic face with eyes and mouth moving according to a parabolic model: Smiling and frowning ...
متن کاملShEMP: A Mobile Framework for Shared Emotion, Music, and Physiology
As we continue to strive toward a deeper understanding of human social interaction, the playing field continues to change beneath our feet. Ever swiftly, in even the last decade, the means by which we interact, the frequency in which we do so, even the meaning of interaction within daily life continues to evolve as humans become connected in novel ways—one need only consider the “Twittersphere”...
متن کاملThe Role of Emotion and Context in Musical Preference
The powerful emotional effects of music increasingly attract the attention of music information retrieval researchers and music psychologists. In the past decades, a gap exists between these two disciplines, and researchers have focused on different aspects of emotion in music. Music information retrieval researchers are concerned with computational tasks such as the classification of music by ...
متن کاملMappingmidi to the Spiralarray: Disambiguating Pitch Spellings
The problem of assigning appropriate pitch spellings is one of the most fundamental problems in the analysis of digital music information. We present an algorithm for nding the optimal spelling based on the Spiral Array model, a geometric model embodying the relations in tonality. The algorithm does not require the key context to be determined. Instead, it uses a center of e ect (c.e.), an inte...
متن کاملMeDJ: Multidimensional Emotion-aware Music Delivery for Adolescent
Music listening is an integral part of many adolescents’ everyday lives, but it is also a time when adolescents are uniquely vulnerable. Emotional-oriented and avoidance through listening to unsuitable music may bring negative emotion to adolescents and increase the level of their depression. We propose MeDJ, a multidimensional emotion-aware music delivery application, which turns adolescents’ ...
متن کامل