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Music Playlist Generation using Facial Expression Analysis and Task Extraction

Sen A., Popat D., Shah H., Kuwor P., Johri E.

Annales Universitatis Mariae Curie-Skłodowska. Sectio AI, Informatica

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2016

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Vol. 16, no. 2

1--6

EN

In day to day stressful environment of IT Industry, there is a truancy for the appropriate relaxation time for all working professionals. To keep a person stress free, various technical or non-technical stress releasing methods are now being adopted. We can categorize the people working on computers as administrators, programmers, etc. each of whom require varied ways in order to ease themselves. The work pressure and the vexation of any kind for a person can be depicted by their emotions. Facial expressions are the key to analyze the current psychology of the person. In this paper, we discuss a user intuitive smart music player. This player will capture the facial expressions of a person working on the computer and identify the current emotion. Intuitively the music will be played for the user to relax them. The music player will take into account the foreground processes which the person is executing on the computer. Since various sort of music is available to boost one's enthusiasm, taking into consideration the tasks executed on the system by the user and the current emotions they carry, an ideal playlist of songs will be created and played for the person. The person can browse the playlist and modify it to make the system more flexible. This music player will thus allow the working professionals to stay relaxed in spite of their workloads.

2

Application of fussion classify for data classification

Duraj A.

Journal of Applied Computer Science

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2013

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Vol. 21, nr 1

39--52

EN

In the published articles and works there are solutions regarding data fusion. However, there is not any verification as for the efficiency of classifiers in the case of many sources of data given simultaneously. It is, seemingly, a very significant problem to be considered in the case of e.g. data fusion in intelligent traffic control. The intention of the author is to prepare the tools for classification of data which come from various sources. They can be sets (data files) prepared by the user of application, but they can also be one (or many) sets from the UCI machine learning repository (http://archive.ics.uci.edu/ml/).

3

Zastosowanie multimodalnej klasyfikacji w rozpoznawaniu stanów emocjonalnych na podstawie mowy spontanicznej

Kamińska D., Pelikant A.

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska

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2012

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nr 3

36-39

PL

Artykuł prezentuje zagadnienie związane z rozpoznawaniem stanów emocjonalnych na podstawie analizy sygnału mowy. Na potrzeby badań stworzona została polska baza mowy spontanicznej, zawierająca wypowiedzi kilkudziesięciu osób, w różnym wieku i różnej płci. Na podstawie analizy sygnału mowy stworzono przestrzeń cech. Klasyfikację stanowi multimodalny mechanizm rozpoznawania, oparty na algorytmie kNN. Średnia poprawność: rozpoznawania wynosi 83%.

EN

The article presents the issue of emotion recognition from a speech signal. For this study, a Polish spontaneous database, containing speech from people of different age and gender, was created. Features were determined from the speech signal. The process of recognition was based on multimodal classification, related to kNN algorithm. The average of accuracy performance was up to 83%.

4

Crisp and Fuzzy Classifiers in the Two-Phase Gas-Liquid Flow Diagnostics

Fiderek P., Jaworski T., Banasiak R., Kucharski J.

Image Processing & Communications

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2012

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Vol. 17, no. 4

385--394

EN

The following paper presents results of common clustering algorithms use, both crisp and fuzzy, for flow pattern recognition of two-phase gas-liquid flows observed in horizontal pipeline. Obtained results of HCM, FCM, and kNN clustering algorithms were presented in a form of confusion matrix and compared via its prediction performance.