Audio is one of important information carriers in the multimedia. It contains abundant semantics and enriches information perception and acquisition. At present, it always uses vision information in the multimedia retrieval, but ignores audio information. In this paper, the problem of audio classification is discussed. The combination of Support Vector Machine and Hidden Markov Model is describ...

NOTE: this is a draft, will be updated once data is out. Our work towards music emotion recognition in MIREX 2013 stems from our best strategy from 2012 and the addition of new melodic audio features, subject of study during the current year. Three audio frameworks – Marsyas, MIR Toolbox and PsySound3, are used to extract the commonly used audio features from the samples. In addition, MELODIA v...

Music on the radio is often interrupted by advertisements or DJ chatter that the listener would prefer not to hear. In this paper, we discuss a straightforward application of perceptually-based audio feature extraction and classification using a support vector machine to automatically differentiate between music and “non-music” audio, so that when non-music is detected the radio might automatic...

In this paper, a support vector machines (SVMs) based method is proposed for content-based audio classification and retrieval. Given a feature set, which in this work is composed of perceptual and cepstral feature, optimal class boundaries between classes are learned from training data by using SVMs. Matches are ranked by using distances from boundaries. Experiments are presented to compare var...

BACKGROUND Despite the widespread availability of computerized decision support systems (CDSSs) in various healthcare settings, evidence on their uptake and effectiveness is still limited. Most barrier studies focus on CDSSs that are aimed at a limited number of decision points within selected small-scale academic settings. The aim of this study was to identify the perceived barriers to using l...

OBJECTIVES As health information is becoming increasingly accessible, social media offers ample opportunities to track, be informed, share and promote health. These authors explore how social media and holistic care may work together; more specifically however, our objective is to document, from different perspectives, how social networks have impacted, supported and helped sustain holistic sel...