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Grill T.,Austrian Research Institute for Artificial Intelligence OFAI | Flexer A.,Austrian Research Institute for Artificial Intelligence OFAI
ICMC 2012: Non-Cochlear Sound - Proceedings of the International Computer Music Conference 2012 | Year: 2012

We describe a visualization strategy that is capable of efficiently representing relevant perceptual qualities of textural sounds. The general aim is to develop intuitive screen- based interfaces representing large collections of sounds, where sound retrieval shall be much facilitated by the exploitation of cross-modal mechanisms of human perception. We propose the use of metaphoric sensory properties that are shared between sounds and graphics, constructing a meaningful mapping of auditory to visual dimensions. For this purpose, we have implemented a visualization using tiled maps, essentially combining low-dimensional projection and iconic representation. To prove the suitability we show detailed results of experiments having been conducted in the form of an online survey. Potential future use in music creation is illustrated by a prototype sound browser application.


Typke R.,Austrian Research Institute for Artificial Intelligence OFAI
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2011

We describe a new method for recognizing notes from monophonic audio, such as sung or whistled queries. Our method achieves results similar to known methods, but without any probabilistic models that would need to be trained. Instead, we define a distance function for audio frames that captures three criteria of closeness which usually coincide with frames belonging to the same note: small pitch difference, small loudness fluctuations between the frames, and the absence of non-pitched frames between the compared frames. We use this distance function for clustering frames such that the total intra-cluster costs are minimized. Criteria for clustering termination include the uniformity of note costs. This new method is fast, does not rely on any particular fundamental frequency estimation method being used, and it is largely independent of the input mode (singing, whistling, playing an instrument). It is already being used successfully for the "query by humming/whistling/playing" search feature on the publicly available collaborative melody directory Musipedia.org. © 2011 Springer-Verlag Berlin Heidelberg.


Flexer A.,Austrian Research Institute for Artificial Intelligence OFAI | Schnitzer D.,Austrian Research Institute for Artificial Intelligence OFAI | Schluter J.,Austrian Research Institute for Artificial Intelligence OFAI
Proceedings of the 13th International Society for Music Information Retrieval Conference, ISMIR 2012 | Year: 2012

We use results from the 2011 MIREX "Audio Music Similarity and Retrieval" task for a meta analysis of the hub phenomenon. Hub songs appear similar to an undesirably high number of other songs due to a problem of measuring distances in high dimensional spaces. Comparing 17 algorithms we are able to confirm that different algorithms produce very different degrees of hubness. We also show that hub songs exhibit less perceptual similarity to the songs they are close to, according to an audio similarity function, than non-hub songs. Application of the recently introduced method of "mutual proximity" is able to decisively improve this situation. © 2012 International Society for Music Information Retrieval.


Widmer G.,Johannes Kepler University | Widmer G.,Austrian Research Institute for Artificial Intelligence OFAI
ACM Transactions on Intelligent Systems and Technology | Year: 2016

This text offers a personal and very subjective view on the current situation of Music Information Research (MIR). Motivated by the desire to build systems with a somewhat deeper understanding of music than the ones we currently have, I try to sketch a number of challenges for the next decade of MIR research, grouped around six simple truths about music that are probably generally agreed on but often ignored in everyday research. © 2016 ACM.


Payr S.,Austrian Research Institute for Artificial Intelligence OFAI
Proceedings - IEEE International Workshop on Robot and Human Interactive Communication | Year: 2010

A field study with a simple robotic companion is being undertaken in three iterations in the framework of a EU FP7 research project. The interest of this study lies in its design: the robotic interface setup is installed in the subjects' homes and video data are collected during ten days. This gives the rare opportunity to study the development of human-robot relationships over time, and the integration of companion technologies into everyday life. This paper outlines the qualitative inductive approach to data analysis, and discusses selected results. The focus here is on the interactional mechanisms of bringing conversations to an end. The paper distinguishes between "closing" as the conversational mechanism for doing this, and "closure" as the social norm that motivates it. We argue that this distinction is relevant for interaction designers insofar as they have to be aware of the compelling social norms that are invoked by a companion's conversational behaviour. © 2010 IEEE.


Jancsary J.,Austrian Research Institute for Artificial Intelligence OFAI | Matz G.,Vienna University of Technology
Journal of Machine Learning Research | Year: 2011

We investigate minimization of tree-reweighted free energies for the purpose of obtaining approximate marginal probabilities and upper bounds on the partition function of cyclic graphical models. The solvers we present for this problem work by directly tightening tree-reweighted upper bounds. As a result, they are particularly efficient for tree-reweighted energies arising from a small number of spanning trees. While this assumption may seem restrictive at first, we show how small sets of trees can be constructed in a principled manner. An appealing property of our algorithms, which results from the problem decomposition, is that they are embarrassingly parallel. In contrast to the original message passing algorithm introduced for this problem, we obtain global convergence guarantees. Copyright 2011 by the authors.


Payr S.,Austrian Research Institute for Artificial Intelligence OFAI
Applied Artificial Intelligence | Year: 2011

The special issue of Applied Artificial Intelligence brings together results of and reflections on the research work undertaken in the project Social Engagement with Robots and Agents (SERA) during the years 2009 and 2010. The description of the setup and the field study is provided by the article, Describing the Interactive Domestic Robot Setup for the SERA Project. The article Theory of Companions: What Can Theoretical Models Contribute to Applications and Understanding of Human-Robot Interaction? begins, as did the project, with a review of social psychological theories of human-human relationships. The article, From Data to Design, addresses reflections on methodology in analyzing human-robot interaction from the engineers' perspective. It takes a critical look at qualitative methods of data analysis and proposes the narrative method as a path from episodic data to design. The final article, On the Nature of Engineering Social Artificial Companions, carries on the development perspective.


Schnitzer D.,Austrian Research Institute for Artificial Intelligence OFAI | Flexer A.,Austrian Research Institute for Artificial Intelligence OFAI | Schedl M.,Johannes Kepler University | Widmer G.,Johannes Kepler University
Journal of Machine Learning Research | Year: 2012

'Hubness' has recently been identified as a general problem of high dimensional data spaces, manifesting itself in the emergence of objects, so-called hubs, which tend to be among the k nearest neighbors of a large number of data items. As a consequence many nearest neighbor relations in the distance space are asymmetric, that is, object y is amongst the nearest neighbors of x but not vice versa. The work presented here discusses two classes of methods that try to symmetrize nearest neighbor relations and investigates to what extent they can mitigate the negative effects of hubs. We evaluate local distance scaling and propose a global variant which has the advantage of being easy to approximate for large data sets and of having a probabilistic interpretation. Both local and global approaches are shown to be effective especially for high-dimensional data sets, which are affected by high hubness. Both methods lead to a strong decrease of hubness in these data sets, while at the same time improving properties like classification accuracy. We evaluate the methods on a large number of public machine learning data sets and synthetic data. Finally we present a real-world application where we are able to achieve significantly higher retrieval quality. © 2012 Dominik Schnitzer, Arthur Flexer, Markus Schedl and Gerhard Widmer.


Feldbauer R.,Austrian Research Institute for Artificial Intelligence OFAI | Flexer A.,Austrian Research Institute for Artificial Intelligence OFAI
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2016

Hubs and anti-hubs are points that appear very close or very far to many other data points due to a problem of measuring distances in high-dimensional spaces. Hubness is an aspect of the curse of dimensionality affecting many machine learning tasks. We present the first large scale empirical study to compare two competing hubness reduction techniques: scaling and centering. We show that scaling consistently reduces hubness and improves nearest neighbor classification, while centering shows rather mixed results. Support vector classification is mostly unaffected by centering-based hubness reduction. © Springer International Publishing Switzerland 2016.


Rank S.,Austrian Research Institute for Artificial Intelligence OFAI
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2013

In this chapter, a scenario-based analysis of the guiding vision of a virtual butler is presented. After introducing the concept of scenario-based analysis for comparing agent-based technology design, we use the characterization of the scenario hinted at in the vision document to discuss several technological issues that arise from it. By disregarding non-technical issues, we arrive at problems (or rather challenges) of technology in a wide sense that could be steps in the direction of the virtual butler. The order of presentation of these challenges is based on a subjective estimation of the complexity involved in arriving at the competence required for a virtual butler. © Springer-Verlag Berlin Heidelberg 2013.

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