Gregor Strle

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The paper presents two vital aspects of the EthnoMuse digital library. We first present the development of a flexible data model through FRBRoo and CIDOC CRM conceptualization of processes and relations in folk song and music realizations. The approach is novel in that it conceptualizes and integrates various folkloristic and ethnomusicological materials,(More)
The paper presents the development of EthnoMuse: multimedia digital library of Slovenian folk music and dance culture. The main scope of the project concerns the digitization of production and post-production processes that relate to collecting, documenting and archiving of folk heritage and development of multimedia applications for various content types(More)
The paper presents a new dataset that captures the effect of mood on visual and auditory perception of music. With an online survey, we have collected a dataset of over 6600 responses capturing users’ mood, emotions evoked and expressed by music and the perception of color with regard to emotions and music. We describe the methodology of gathering the(More)
A simple and efficient method allows the synthesis of solutions of high-purity hydrogen trioxide (HOOOH), released in the low-temperature methytrioxorhenium(VII) (MTO)-catalyzed transformation of the ozonized polystyrene-supported dimethylphenylsilane. High-purity hydrogen trioxide solutions in diethyl ether, separated from the polymer and free of any(More)
The paper presents a new dataset of mood-dependent and color responses to music. The methodology of gath-ering user responses is described along with two new inter-faces for capturing emotional states: the MoodGraph and MoodStripe. An evaluation study showed both inter-faces have significant advantage over more traditional methods in terms of intuitiveness,(More)
This paper presents a new dataset gathered containing perceived and induced emotions for 200 audio clips. The gathered dataset also provides users’ association of color for each clip, along with users’ demographic and personal data, such as users’ emotion state, preferred genres, music experience and daily inference, and others. With an online survey we(More)