Adaptace systemu rozpoznavani plynule cestiny na konkretniho recnika.

To increase the recognition rate of speaker independent system for a particular speaker with the use of relatively small amount of data, methods called recogniser adaptation to a new speaker are used. Study of these methods, design of a particular method and its corrections for the Czech language are the topics of this thesis. Let us note that the author does not know any work dealing with the recogniser adaptation to a new speaker for the Czech or other Slavic language. Outline of used methods for recogniser adaptation to a new speaker and their categorisation is presented in this thesis. The outline is based on thorough study of articles and paper from corresponding periodicals and world conferences. The task of recogniser adaptation to a new speaker, presented in this thesis, can be characterised as batch, supervised, text independent adaptation with the use of independent adaptation data set. For this purpose the method of maximum a posteriori (MAP) method is proposed. MAP method is based on the Bayesian approach. This method uses models from the SI base system and considers their parameters as a priori knowledge. Then, with the use of adaptation data set it tries to estimate the a posteriori information that is new model parameters, which are then better suited to the voice of a new speaker. Adaptation data set is much smaller than the amount of data needed for training of the base system. As the test results of the MAP method showed, the increase of the recognition rate reached did not match presumption. Analysis showed that the cause of this failure is undertraining of some parameters due to small amount of adaptation data for these parameters. The number of adapted parameters is too high and thus for some of them few or even no adaptation data are available. It is caused by rising number of basic phonetic units (triphones) and by bigger richness of the Czech language. For solution of this problem the correction of the MAP method - the parameter tying method - is proposed. This method uses high correlation between phonetically close parameter. Using this approach it is possible to replace undertrained model by estimates obtained using other parameter and knowledge about their mutual relationship. By implementation of this method better recognition results have been reached. These results can be considered as success and are comparable with the results presented in reference papers.Summary in EnglishAvailable from STL, Prague, CZ / NTK - National Technical LibrarySIGLECZCzech Republi

Digitalization of management processes in scientific and educational organizations

Document circulation and communication between organizations, their structural subdivisions and employees are increasingly being made on the basis of infocommunication technologies and paperless digital approaches. This article provides a review of existing information systems, the main activities of scientific and educational organizations, ways of interaction with state and commercial enterprises. The analysis of general types of administrative and economic, financial activity, as well as scientific, educational, publishing activities, specialized for academic institutions is given. It is considered domestic, works dedicated to automation of processes and the introduction of information systems in scientific and educational organizations, as well as existing foreign technologies for automating the learning process. Most existing Russian and foreign systems include modules that provide electronic document management and communication. Despite existing standards, scientific and educational organizations are difficult to unify, due to their specialization and historically established traditions. Due to the multifaceted activity of scientific and educational organizations, individual proprietary software modules were created for the most demanded processes, which led to the problem of integrating modules developed at different times for different services accumulating databases with duplicate information. Information is provided on the corporate information systems developed in SPIIRAS, distinguished by the use of biometric contactless means of interaction with users and personalized maintenance scenarios

Justification of the technical requirements of a fully functional modular robot

Modular robots are characterized by limited built-in resources necessary for communication, connection and movement of modules, when performing reconfiguration tasks at rigidly interconnected elements. In developing the technological fundamentals of designing modular robots with pairwise connection mechanisms, we analysed modern hardware and model algorithms typical of a fully functional robot, which provide independent locomotion, communication, navigation, decentralized power and control. A survey of actuators, batteries, sensors, communication means, suitable for modular robotics is presented

A Multimodal User Interface for an Assistive Robotic Shopping Cart

This paper presents the research and development of the prototype of the assistive mobile information robot (AMIR). The main features of the presented prototype are voice and gesture-based interfaces with Russian speech and sign language recognition and synthesis techniques and a high degree of robot autonomy. AMIR prototype’s aim is to be used as a robotic cart for shopping in grocery stores and/or supermarkets. Among the main topics covered in this paper are the presentation of the interface (three modalities), the single-handed gesture recognition system (based on a collected database of Russian sign language elements), as well as the technical description of the robotic platform (architecture, navigation algorithm). The use of multimodal interfaces, namely the speech and gesture modalities, make human-robot interaction natural and intuitive, as well as sign language recognition allows hearing-impaired people to use this robotic cart. AMIR prototype has promising perspectives for real usage in supermarkets, both due to its assistive capabilities and its multimodal user interface.Peer reviewe

Proč vvyužívat polohové příznaky při segmentaci jater s využitím konvolučních neuronových sítí

The calculation of liver volume is primarily based on Computed Tomography. Unfortunately, automatic segmentation algorithms based on handcrafted features tend to leak segmented objects into surrounding tissues like the heart or the spleen. Currently, convolutional neural networks are widely used in various applications of computer vision including image segmentation, while providing very promising results. In our work, we utilize robustly segmentable structures like the spine, body surface, and sagittal plane. They are used as key points for position estimation inside the body. The signed distance fields derived from these structures are calculated and used as an additional channel on the input of our convolutional neural network, to be more specific U-Net, which is widely used in medical image segmentation tasks. Our work shows that this additional position information improves the results of the segmentation. We test our approach in two experiments on two public datasets of Computed Tomography images. To evaluate the results, we use the Accuracy, the Hausdorff distance, and the Dice coefficient. Code is publicly available at: https://gitlab.com/hachaf/liver-segmentation.git