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Title:
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Robust clustering of data collected via crowdsourcing
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Author:
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Pagès Zamora, Alba Maria; Giannakis, Georgios B.; López Valcarce, Roberto; Giménez Febrer, Pedro Juan
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Other authors:
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Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions; Universitat Politècnica de Catalunya. SPCOM - Grup de Recerca de Processament del Senyal i Comunicacions |
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Abstract:
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Abstract:
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Crowdsourcing approaches rely on the collection of multiple individuals to solve problems that require analysis of large data sets in a timely accurate manner. The inexperience of participants or annotators motivates well robust techniques. Focusing on clustering setups, the data provided by all an- notators is suitably modeled here as a mixture of Gaussian components plus a uniformly distributed random variable to capture outliers. The proposed algorithm is based on the expectation-maximization algorithm and allows for soft as- signments of data to clusters, to rate annotators according to their performance, and to estimate the number of Gaussian components in the non-Gaussian/Gaussian mixture model, in a jointly manner. |
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Abstract:
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Peer Reviewed |
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Subject(s):
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-Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la parla i del senyal acústic
-Automatic speech recognition
-Crowdsourcing
-Gaussian plus non-Gaussian mixture
-Outlier
-EM algorithm
-Bayesian information criterion
-Reconeixement automàtic de la parla |
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Rights:
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Document type:
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Article - Submitted version
Conference Object |
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