14,912 research outputs found

    Multimedia search without visual analysis: the value of linguistic and contextual information

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    This paper addresses the focus of this special issue by analyzing the potential contribution of linguistic content and other non-image aspects to the processing of audiovisual data. It summarizes the various ways in which linguistic content analysis contributes to enhancing the semantic annotation of multimedia content, and, as a consequence, to improving the effectiveness of conceptual media access tools. A number of techniques are presented, including the time-alignment of textual resources, audio and speech processing, content reduction and reasoning tools, and the exploitation of surface features

    Non score-dependency: Theory and assessment

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    Untrained listeners demonstrate implicit knowledge of syntactic patterns and principles. Untrained generative music ability, for example singing, humming, and whistling, is a largely unconscious or intuitive application of these patterns and principles. From the viewpoint of embodied cognition, listening to music should evoke an internal representation or motor image which, together with the perception of organized music, should form the basis of musical cognition. Indeed, that is what listeners demonstrate when they sing, hum, or whistle familiar and unfamiliar tunes or when they vocally or orally improvise continuations to interrupted phrases. Research on vocal improvisation using continuations sung to an interrupted musical phrase, has shown that one’s cultural background influences the music generated. That should be the case for instrumentalists as well: when they play familiar or unfamiliar tunes by ear in different keys (transposition) or when they improvise variations, accompaniments, or continuations to interrupted phrases, the music they generate should reflect the same cognitive structures as their oral improvisations. This study is attempting to validate a test of (non) scoredependency that will enable assessment of the music student’s implicit knowledge of these structures during performance on the principal instrument

    The Economic Consequences of IFRS: The Impact of IAS 32 on Preference Shares in the Netherlands

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    The consequences of international accounting standards are likely to reach beyond the impact on financial statements. This paper demonstrates one of the economic implications of international standards. We focus on the impact of the IFRS regulation on preference shares (IAS 32) in the Netherlands. IAS 32 causes most preference shares to lose their classification as equity and these shares will hence be classified as liabilities. We document that for Dutch firms with preferred stock outstanding, the reclassification will on average increase the reported debt ratio by 35%. We find that 71% of the firms that are affected by IAS 32 buy back their preference shares or alter the specifications of the preference shares in such a way that the classification as equity can be maintained. The main determinant of the decision whether to give these consequences to IAS 32 is the magnitude of the impact of IAS 32 on a firm’s debt ratio. We conclude that IFRS does not only lead to a decrease in the use of financial instruments that otherwise would have added to the capital structure diversity, but also changes firms’ real capital structure.IFRS;Accounting Changes;Economic Consequences;IAS 32;Magnitude Effect;Preference Shares

    The Way We Measure: Comparison of Methods to Derive Radial Surface Brightness Profiles

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    The breaks and truncations in the luminosity profile of face-on spiral galaxies offer valuable insights in their formation history. The traditional method of deriving the surface photometry profile for face-on galaxies is to use elliptical averaging. In this paper, we explore the question whether elliptical averaging is the best way to do this. We apply two additional surface photometry methods, one new: principle axis summation, and one old that has become seldom used: equivalent profiles. These are compared to elliptically averaged profiles using a set of 29 face-on galaxies. We find that the equivalent profiles match extremely well with elliptically averaged profiles, confirming the validity of using elliptical averaging. The principle axis summation offers a better comparison to edge-on galaxies.Comment: Accepted for publication by Monthly Notices of the R.A.S. A hi-res version is available at http://www.astro.rug.nl/~vdkruit/Petersetal-VI.pd

    Speech-based recognition of self-reported and observed emotion in a dimensional space

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    The differences between self-reported and observed emotion have only marginally been investigated in the context of speech-based automatic emotion recognition. We address this issue by comparing self-reported emotion ratings to observed emotion ratings and look at how differences between these two types of ratings affect the development and performance of automatic emotion recognizers developed with these ratings. A dimensional approach to emotion modeling is adopted: the ratings are based on continuous arousal and valence scales. We describe the TNO-Gaming Corpus that contains spontaneous vocal and facial expressions elicited via a multiplayer videogame and that includes emotion annotations obtained via self-report and observation by outside observers. Comparisons show that there are discrepancies between self-reported and observed emotion ratings which are also reflected in the performance of the emotion recognizers developed. Using Support Vector Regression in combination with acoustic and textual features, recognizers of arousal and valence are developed that can predict points in a 2-dimensional arousal-valence space. The results of these recognizers show that the self-reported emotion is much harder to recognize than the observed emotion, and that averaging ratings from multiple observers improves performance