11,633 research outputs found
Processing and Linking Audio Events in Large Multimedia Archives: The EU inEvent Project
In the inEvent EU project [1], we aim at structuring, retrieving, and sharing large archives of networked, and dynamically changing, multimedia recordings, mainly consisting of meetings, videoconferences, and lectures. More specifically, we are developing an integrated system that performs audiovisual processing of multimedia recordings, and labels them in terms of interconnected “hyper-events ” (a notion inspired from hyper-texts). Each hyper-event is composed of simpler facets, including audio-video recordings and metadata, which are then easier to search, retrieve and share. In the present paper, we mainly cover the audio processing aspects of the system, including speech recognition, speaker diarization and linking (across recordings), the use of these features for hyper-event indexing and recommendation, and the search portal. We present initial results for feature extraction from lecture recordings using the TED talks. Index Terms: Networked multimedia events; audio processing: speech recognition; speaker diarization and linking; multimedia indexing and searching; hyper-events. 1
Flabase: towards the creation of a flamenco music knowledge base
Online information about flamenco music is scattered overdifferent sites and knowledge bases. Unfortunately, thereis no common repository that indexes all these data. Inthis work, information related to flamenco music is gath-ered from general knowledge bases (e.g., Wikipedia, DB-pedia), music encyclopedias (e.g., MusicBrainz), and spe-cialized flamenco websites, and is then integrated into anew knowledge base called FlaBase. As resources fromdifferent data sources do not share common identifiers, aprocess of pair-wise entity resolution has been performed.FlaBase contains information about 1,174 artists, 76pa-los(flamenco genres), 2,913 albums, 14,078 tracks, and771 Andalusian locations. It is freely available in RDF andJSON formats. In addition, a method for entity recognitionand disambiguation for FlaBase has been created. The sys-tem can recognize and disambiguate FlaBase entity refer-ences in Spanish texts with an f-measure value of 0.77. Weapplied it to biographical texts present in Flabase. By usingthe extracted information, the knowledge base is populatedwith relevant information and a semantic graph is createdconnecting the entities of FlaBase. Artists relevance is thencomputed over the graph and evaluated according to a fla-menco expert criteria. Accuracy of results shows a highdegree of quality and completeness of the knowledge base
FolkRank: A Ranking Algorithm for Folksonomies
In social bookmark tools users are setting up lightweight conceptual structures called folksonomies. Currently, the information retrieval support is limited. We present a formal model and a new search algorithm for folksonomies, called FolkRank, that exploits the structure of the folksonomy. The proposed algorithm is also applied to find communities within the folksonomy and is used to structure search results. All findings are demonstrated on a large scale dataset. A long version of this paper has been published at the European Semantic Web Conference 2006
Visualizing and Interacting with Concept Hierarchies
Concept Hierarchies and Formal Concept Analysis are theoretically well
grounded and largely experimented methods. They rely on line diagrams called
Galois lattices for visualizing and analysing object-attribute sets. Galois
lattices are visually seducing and conceptually rich for experts. However they
present important drawbacks due to their concept oriented overall structure:
analysing what they show is difficult for non experts, navigation is
cumbersome, interaction is poor, and scalability is a deep bottleneck for
visual interpretation even for experts. In this paper we introduce semantic
probes as a means to overcome many of these problems and extend usability and
application possibilities of traditional FCA visualization methods. Semantic
probes are visual user centred objects which extract and organize reduced
Galois sub-hierarchies. They are simpler, clearer, and they provide a better
navigation support through a rich set of interaction possibilities. Since probe
driven sub-hierarchies are limited to users focus, scalability is under control
and interpretation is facilitated. After some successful experiments, several
applications are being developed with the remaining problem of finding a
compromise between simplicity and conceptual expressivity
Unsupervised, Knowledge-Free, and Interpretable Word Sense Disambiguation
Interpretability of a predictive model is a powerful feature that gains the
trust of users in the correctness of the predictions. In word sense
disambiguation (WSD), knowledge-based systems tend to be much more
interpretable than knowledge-free counterparts as they rely on the wealth of
manually-encoded elements representing word senses, such as hypernyms, usage
examples, and images. We present a WSD system that bridges the gap between
these two so far disconnected groups of methods. Namely, our system, providing
access to several state-of-the-art WSD models, aims to be interpretable as a
knowledge-based system while it remains completely unsupervised and
knowledge-free. The presented tool features a Web interface for all-word
disambiguation of texts that makes the sense predictions human readable by
providing interpretable word sense inventories, sense representations, and
disambiguation results. We provide a public API, enabling seamless integration.Comment: In Proceedings of the the Conference on Empirical Methods on Natural
Language Processing (EMNLP 2017). 2017. Copenhagen, Denmark. Association for
Computational Linguistic
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