Is it myself in the mirror?

in English A beautiful and healthy body now indicates a happy and contented life, and that is why our society is so obsessed by it. It was transformed into a commercial object, and the borders to which we can manipulate with it are pushed even further. At the same time, many people realize the necessity of cooperation with the body in order to reach a physical and mental health. Voices are heard calling for prevention of exploitation of human bodies and against the lowering of human dignity. We can see showing up different kinds of oriental philosophy, psychosomatic medicine or psychoterapeutic approaches targeted at the body, which are trying to outweigh the trends treating the body as a mere commodity. In spite of those efforts, the number of people with impaired perception and experiencing of their own body is still growing. The most frequent and most discussed are the eating disorders, which endanger seriously all aspects of a person's life. Most of the disorders will develop during adolescence, and that is why in my research I focused on the mapping of corporal experience of young people. In my work I employed the grounded theory method, or a qualitative research. The main research method used is semi-structured interview. The theoretical part consists of a philosophical historical and social..

Body: the object of aesthetisantion

Katedra psychologieFaculty of EducationPedagogická fakult

Metoda pro segmentaci audio signálů podle řečníka

Článek se zabývá úlohou segmentace nahrávky podle řečníka. Cílem úlohy je vydělit z nahrávky úseky, z nichž každý obsahuje co nejdelší promluvu vyslovenou pouze jedniným řečníkem. Metoda popsaná v tomto článku nepotřebuje žádné apriorní znalosti o řečníkovi ani o charakteristikách řečového signálu.The paper deals with the problem of speaker-based segmentation. The goal of this task is to extract homogeneous segments containing the longest possible utterances produced by a single speaker. In the method presented here, no assumption is made about prior knowledge of the speaker or speech signal characteristics (there is no speaker model, no speech model, even the number of speakers in the recording is not known)

Nahrávání a anotace českého řečového korpusu

The paper reassumes our papers presented at the previous TSD workshops and concerns the Czech speech corpus which is being developed at the Department of Cybernetics, University of West Bohemia in Pilsen. It describes procedures of the corpus recording and annotation

Modifikovaný DISTBIC algoritmus pro detekci změny řečníka

Článek se zabývá problémem automatické detekce změny řečníka. V článku je navržen modifikovaný algoritmus nazývaný MDISTBIC, který je založen na vzdálenosti mezi sousedními segmenty. Navržený algoritmus vychází z algoritmu DISTBIC, který je modifikován tak, aby bylo dosaženo větší výkonnosti. Oba algoritmy (jak DISTBIC, tak MDISTBIC) jsou testovány v řadě experimentů. Jak ukazují výsledky, je ve většině testů algoritmus MDISTBIC mnohem účinější než algoritmus DISTBIC.The paper deals with the problem of automatic speaker change detection. A metric-based algorithm, called MDISTBIC, which means Modified DISTBIC, is proposed in this paper. The algorithm originates from the DISTBIC algorithm and modifies it in order to reach a higher efficiency. Both the DISTBIC and the MDISTBIC methods are tested in a number of experiments. As the results show, the MDISTBIC algorithm is more efficient than the DISTBIC algorithm in a majority of tests

Identifikace řečníka na základě vektorové kvantizace

In this paper a method of text-independent speaker recognition using discrete vector quantization is presented. The identification experiments were performed in a closed set of 599 speakers and two various types of features were tested: cepstral mean subtraction coeficients and mel-frequency cepstral coeficients. The effect of the various codebook size on the speaker identification performance was investigated

Porovnání několika procedur verifikace řečníka založených na GMM

Článek pojednává o závislosti mezi identifikací řečníka a množstvím dat pro testování. V článku jsou prezentovány tři identifikační procedury.The paper deals with the dependence between the speaker identification performance and the amount of test data. Three speaker identification procedures based on hidden Markov models (HMMs) of phonemes are presented here. One, which is quite commonly used in the speaker recognition systems based on HMMs, uses the likelihood of the whole utterance for speaker identification. The other two that are proposed in this paper are based on the majority voting rule. The experiments were performed for two different situations: either both training and test data were obtained from the same channel, or they were obtained from different channels. All experiments show that the proposed speaker identification procedure based on the majority voting rule for sequences of phonemes allows us to reduce the amount of test data necessary for successful speaker identification

Konstrukce modelu okolí pro verifikaci řečníka využívající GMM

V článku je prezentována metoda verifikace řečníka využívající Gaussovských hustotních směsí. Metoda využívá model okolí složený z několika submodelů. V článku jsou uvedeny různé přístupy pro konstrukci složeného modelu: logaritmus pravděpodobnosti složeného modelu je určen buď jako průměr logaritmů pravděpodobností dílčích submodelů, a nebo jako maximum z logaritmů pravděpodobností dílčích submodelů. Provedené experimety ukázaly, že prvně jmenovaný přístup umožňuje dosáhnout lepších výsledků.A method of speaker verification based on Gaussian mixture models is presented in this paper. The method works with a background model which is composed of several submodels. Several different approaches for construction of the background model from the submodels are introduced here: the log likelihood of the background model is determined either as the average of the log likelihoods of the particular submodels, or a maximum from the log likelihoods of the particular submodels is selected. A large number of experiments was performed in order to find which of the approaches gives the best result. All experiments show that procedures which use a maximum of the log likelihoods of the background submodels have better performance than the procedure which uses the average log likelihood

Detekce změny řečníka s využitím vzdálenostního přístupu

Článek se zabývá problémem automatické detekce změny řečníka. Je navržen nový vzdálenostní algoritmus nazývaný AlgBICMap. Tento algoritmus umožňuje vytvořit BIC (Bayessovské informační kritérium) mapu, která nám dovoluje účinně detekovat oblasti řeči jednotlivých řečníků. Ve srovnání s typickými vzdálenostními přístupy spočívá výhoda navrženého algoritmu v jeho robustnosti, protože algoritmus užívá více informace, nejen informaci poskytnutou sousedními okny. Navíc AlgBICMap algoritmus lze využít také pro úlohy sledování řečníka.The paper deals with the problem of automatic speaker change detection. A new metric-based algorithm, called AlgBICMap algorithm, is proposed in this paper. The AlgBICMap algorithm allows to create a map of BIC (Bayessian Information Criterion), which enables us to detect efficiently fields of speech of individual speakers. In comparison with a typical metric-based approach, the advantage of the proposed algorithm is its robustness because it uses more information, not only information provided by adjacent windows. In addition to that, the AlgBICMap algorithm can be used also for speaker tracking tasks