Polish Japanese Academy of Information Technology

Bytom, Poland

Polish Japanese Academy of Information Technology

Bytom, Poland
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Wolk K.,Polish Japanese Academy of Information Technology | Marasek K.,Polish Japanese Academy of Information Technology
Advances in Intelligent Systems and Computing | Year: 2017

The multilingual nature of the world makes translation a crucial requirement today. Parallel dictionaries constructed by humans are a widely-available resource, but they are limited and do not provide enough coverage for good quality translation purposes, due to out-of-vocabulary words and neologisms. This motivates the use of statistical translation systems, which are unfortunately dependent on the quantity and quality of training data. Such systems have a very limited availability especially for some languages and very narrow text domains. Is this research we present our improvements to current quasi-comparable corpora mining methodologies by re-implementing the comparison algorithms, introducing a tuning script and improving performance using GPU acceleration. The experiments are conducted on lectures text domain and bi-data is extracted from web crawl from the WWW. The modifications made a positive impact on the quality and quantity of mined data and on the translation quality as well and used the BLEU, NIST and TER metrics. By defining proper translation parameters to morphologically rich languages we improve the translation quality and draw the conclusions. © Springer International Publishing Switzerland 2017.


Kacprzak M.,University of Bialystok | Starosta B.,Polish Japanese Academy of Information Technology | Wegrzyn-Wolska K.,ESIGETEL
Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) | Year: 2015

The paper is devoted to the problem of modeling human attitudes towards imprecise ideas. A metaset is used for representing an imprecise concept and Opinion Mining techniques are applied to build a preference function which reflects someone's attitude towards the idea.The preferences are then evaluated as real numbers for the sake of comparison and selection of the best matching instance. The core of the idea of representing any imprecise concept with a metaset lies in splitting it into a treelike hierarchy of related sub-concepts. The nodes of the tree determine the membership degrees for metaset members and they are natural language terms which also describe reasons for some particular member to satisfy the represented idea. The Opinion Mining allows for automatic gathering and evaluation of opinions from the Internet. The proposed mechanism is applied to solve the problem of selecting the car best matching the imprecise idea of a good car for a lady. This approach can be applied in a decision support systems that helps both marketers and customers. © Springer International Publishing Switzerland 2015.


Bialasiewicz J.T.,Polish Japanese Academy of Information Technology | Bialasiewicz J.T.,University of Colorado at Denver
IEEE International Conference on Industrial Informatics (INDIN) | Year: 2017

Cyber-Physical Systems (CPS) require tools that enable development of design methodology that supports analysis and modeling of Interaction Dynamics of Concurrent Processes (IDCP) represented by the measurement data provided by smart acquisition systems. In this paper, are presented some results of the project aiming at the development of algorithms and software tools that could detect short-lived temporal interaction of concurrent processes. The analysis is performed in time-frequency domain using wavelet tools. Some possibilities of such analysis are presented using an example of coherence investigation of concurrent biomedical processes. © 2016 IEEE.


Wolk K.,Polish Japanese Academy of Information Technology | Wolk A.,Polish Japanese Academy of Information Technology
Advances in Intelligent Systems and Computing | Year: 2017

Several natural languages have had much processing, but the problem of limited linguistic resources remains. Manual creation of parallel corpora by humans is rather expensive and very time consuming. In addition, language data required for statistical machine translation (SMT) does not exist in adequate capacity to use its statistical information to initiate the research process. On the other hand, applying unsubstantiated approaches to build the parallel resources from multiple means like comparable corpora or quasi-comparable corpora is very complicated and provides rather noisy output. These outputs of the process would later need to be reprocessed, and in-domain adaptations would also be required. To optimize the performance of these algorithms, it is essential to use a quality parallel corpus for training of the end-to-end procedure. In the present research, we have developed a methodology to generate an accurate parallel corpus from monolingual resources through the calculation of compatibility between the results of machine translation systems. We have translations of huge, single-language resources through the application of multiple translation systems and the strict measurement of translation compatibility with rules based on the Levenshtein distance. The results produced by such an approach are very favorable. All the monolingual resources that we obtained were taken from the WMT16 conference for Czech to generate the parallel corpus, which improved translation performance. © Springer International Publishing AG 2017.


Wolk K.,Polish Japanese Academy of Information Technology | Wolk A.,Polish Japanese Academy of Information Technology
Advances in Intelligent Systems and Computing | Year: 2017

It has become essential to have precise translations of texts from different parts of the world, but it is often difficult to fill the translation gaps as quickly as might be needed. Undoubtedly, there are multiple dictionaries that can help in this regard, and various online translators exist to help cross this lingual bridge in many cases, but even these resources can fall short of serving their true purpose. The translators can provide a very accurate meaning of given words in a phrase, but they often miss the true essence of the language. The research presented here describes a method that can help close this lingual gap by extending certain aspects of the alignment task for WMT16. It is possible to achieve this goal by utilizing different classifiers and algorithms and by use of advanced computation. We carried out various experiments that allowed us to extract parallel data at the sentence level. This data proved capable of improving overall machine translation quality. © Springer International Publishing AG 2017.


Klec M.,Polish Japanese Academy of Information Technology
Computer Science | Year: 2017

To deliver better recommendations, music information systems need to go beyond standard methods for the prediction of musical taste. Tracking the listener's emotions is one way to improve the quality of recommendations. This can be achieved explicitly by asking the listener to report his/her emotional state or implicitly by tracking the context in which the music is heard. However, the factors that induce particular emotions vary among individuals. This paper presents the initial research on the influence of an individual's personality on his or her choice of music. The psychological profile of a group of 16 students was determined by a questionnaire. The participants were asked to label their own music collections, listen to the music, and mark their emotions using a custom application. Statistical analysis revealed correlations between low-level audio features, personality types, and the emotional states of the students.


Slawianowski J.J.,Polish Japanese Academy of Information Technology | Kotowski R.K.,Polish Japanese Academy of Information Technology
Zeitschrift fur Angewandte Mathematik und Physik | Year: 2017

The classical mechanics of large molecules and fullerenes is studied. The approach is based on the model of collective motion of these objects. The mixed Lagrangian (material) and Eulerian (space) description of motion is used. In particular, the Green and Cauchy deformation tensors are geometrically defined. The important issue is the group-theoretical approach to describing the affine deformations of the body. The Hamiltonian description of motion based on the Poisson brackets methodology is used. The Lagrange and Hamilton approaches allow us to formulate the mechanics in the canonical form. The method of discretization in analytical continuum theory and in classical dynamics of large molecules and fullerenes enable us to formulate their dynamics in terms of the polynomial expansions of configurations. Another approach is based on the theory of analytical functions and on their approximations by finite-order polynomials. We concentrate on the extremely simplified model of affine deformations or on their higher-order polynomial perturbations. © 2017, The Author(s).


Polkowski L.T.,Polish Japanese Academy of Information Technology
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2016

Zdzisław Pawlak influenced our thinking about uncertainty by borrowing the idea of approximation from geometry and topology and carrying those ideas into the realm of knowledge engineering. In this way, simple and already much worn out mathematical notions, gained a new life given to them by new notions of decision rules and algorithms, complexity problems, and problems of optimization of relations and rules. In his work, the author would like to present his personal remembrances of how his work was influenced by Zdzisław Pawlak interlaced with discussions of highlights of research done in enliving classical concepts in new frameworks, and next, he will go to more recent results that stem from those foundations, mostly on applications of rough mereology in behavioral robotics and classifier synthesis via granular computing. © Springer International Publishing AG 2016.


Brocki L.,Polish Japanese Academy of Information Technology | Marasek K.,Polish Japanese Academy of Information Technology
Archives of Acoustics | Year: 2015

This paper describes a Deep Belief Neural Network (DBNN) and Bidirectional Long-Short Term Memory (LSTM) hybrid used as an acoustic model for Speech Recognition. It was demonstrated by many independent researchers that DBNNs exhibit superior performance to other known machine learning frameworks in terms of speech recognition accuracy. Their superiority comes from the fact that these are deep learning networks. However, a trained DBNN is simply a feed-forward network with no internal memory, unlike Recurrent Neural Networks (RNNs) which are Turing complete and do posses internal memory, thus allowing them to make use of longer context. In this paper, an experiment is performed to make a hybrid of a DBNN with an advanced bidirectional RNN used to process its output. Results show that the use of the new DBNN-BLSTM hybrid as the acoustic model for the Large Vocabulary Continuous Speech Recognition (LVCSR) increases word recognition accuracy. However, the new model has many parameters and in some cases it may suffer performance issues in real-time applications. Copyright © 2015 by PAN - IPPT.


Klec M.,Polish Japanese Academy of Information Technology
Studies in Computational Intelligence | Year: 2016

The experiments described in this paper utilize songs in the MIDI format to train Deep Neural Networks (DNNs) for the Automatic Genre Recognition (AGR) problem. The MIDI songs were decomposed into separate instrument groups and converted to audio. Restricted Boltzmann Machines (RBMs) were trained with the individual groups of instruments as a method of pre-training of the final DNN models. The Scattering Wavelet Transform (SWT) was used for signal representation. The paper explains the basics of RBMs and the SWT, followed by a review of DNN pre-training methods that use separate instrument audio. Experiments show that this approach allows building better discriminating models than those that were trained using whole songs. © Springer International Publishing Switzerland 2016.

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