The purpose of this study was to examine the characteristics of Selective Mutism, its possible causes, the strong impact it creates in English learner students, and what teachers could do to help the students who suffer from Selective Mutism.

This study presents detailed phonetic and acoustic analyses of the speech characteristics of two new cases of Foreign Accent Syndrome (FAS). Participants include a 48-year-old female who began speaking with an "Eastern European" accent following a traumatic brain injury, and a 45-year-old male who presented with a "British" accent following a subcortical cerebral vascular accident (CVA). Identical samples of the participants' pre- and post-morbid speech were obtained, thus affording a new level of control in the study of Foreign Accent Syndrome. The speech tasks consisted of oral readings of the Grandfather Passage and 18 real words comprised of the stop consonants /p/, /t/, /k/, /b/, /d/, /g/ combined with the peripheral vowels /i/, /a/ and /u/ and ending in a voiceless stop. Computer-based acoustic measures included: 1) voice onset time (VOT), 2) vowel durations, 3) whole word durations, 4) first, second and third formant frequencies, and 5) fundamental frequency. Formant frequencies were measured at three points in the vowel duration: a) 20%, b) 50%, and c) 80% to assess differences in vowel 'onglides' and 'offglides'. The phonetic analysis provided perceptual identification of the major phonetic features associated with the foreign quality of participant's FAS speech, while acoustic measures allowed precise quantification of these features. Results indicated evidence of backing of consonant and vowel productions for both participants. The implications for future research and clinical applications are also considered.

По мере развития идей инклюзивного образования остро встает вопрос изучения и сопровождения детей с ограниченными возможностями здоровья. Особое место здесь занимают дети с менее выраженными и более перспективными в части коррекции имеющихся нарушений, в первую очередь, дети и подростки с тяжелыми нарушениями речи. В статье описываются психологические особенности жизнестойкости подростков с тяжелыми нарушениями речи (ТНР). С опорой на исследования Т.Н. Волковской, В.А. Калягина, С.В. Лауткиной, Р.Е. Левиной, Т.С. Овчинниковой, Г.Х. Юсуповой и др., в статье анализируются психологические особенности детей и подростков с ТНР, которые в дальнейшем подтверждаются эмпирическими данными, собранными авторами. Исследование проводилось с применением модифицированного теста жизнестойкости С. Мадди, опросника «Способы совладающего поведения» Р. Лазаруса и С. Фолкман, личностного опросника Г. Айзенка, методики диагностики самооценки личности Дембо-Рубинштейн. Для выявления расширенного психологического содержания жизнестойкости подростков с ТНР изучались дополнительные психологические характеристики, такие как уровни самооценки и притязаний, экстраверсии-нейротизма, а также способов совладающего поведения. Анализ данных проводился с применением корреляционного и факторного анализа. На основе теоретических и эмпирических данных появляется возможность внести в содержание работы с данной категорией детей и подростков направления деятельности, позволяющие научить их преодолевать трудности, правильно относиться к получаемому опыту, накапливать уверенность в своих силах и осваивать адаптивные способы совладающего поведения. На основе материалов исследования могут быть разработаны рекомендации для педагогов и родителей. / With the development of the ideas of inclusive education is very important for study and supporting children with disabilities. A special place is occupied by children with less severe and more promising in terms of correcting existing violations, primarily children and adolescents with severe speech disorders. The article describes the psychological characteristics of resilience in adolescents with severe speech disorders (SSD). Based on the research of T. N. The Volkov, V. A. Kalyagin, S. V. Laudino, R. E. Levina, T. S. Ovchinnikova, Gulnara Yusupova, and others, the article analyzes the psychological characteristics of children and adolescents with TNR, which further confirmed the empirical data collected by the authors. The study was conducted with the use of a modified test of resilience S. muddy, questionnaire "Ways of coping" by R. Lazarus and S. Folkman, personal questionnaire G. Eysenck, methods of diagnostics of self-identity Dembo-Rubinstein. For identifying enhanced the content of the psychological resilience of adolescents with SSD studied additional psychological characteristics, such as levels of self-esteem and claims of extroversion-neuroticism, as well as ways of coping behavior. The data were analyzed using correlation and factor analysis. Based on theoretical and empirical data an opportunity to amend the content of the work with this category of children and adolescents the interventions that teach them to overcome difficulties, the right attitude to experience, to gain confidence and learn adaptive ways of coping behavior. Based on the research materials can be developed recommendations for teachers and parents.

Speech is the most common and the most fundamental tool used for communication. It has done more for man's progress than any other single factor. Yet this high development of man has been relatively ignored, and for generations speech instruction has been partially neglected in the elementary schools. / "Presented to the Faculty of the School of Education Florida State University." / "In Partial Fulfillment of the Requirements for the Degree of Master of Arts in Education." / "July, 1949." / Advisor: Dr. Robert C. Moon, Major Professor. / Typescript. / Added title page: A two year study of speech instruction of a group of children in Jackson Heights School, Tampa, Florida. / Includes bibliographical references.

Healthcare professionals such as speech and language therapists are expected to change their practice throughout their career. However, from a practice perspective, there is a lack of knowledge around what practice change is, what it really takes, and why there are different trajectories. Consequently, therapists, managers and commissioners lack empirical evidence on which to base decisions about enabling practice change. In addition, intervention researchers lack basic sociological research around implementation that could inform their research designs, reporting and impact. This case-based sociological inquiry, underpinned by critical realist assumptions, was designed to address this knowledge gap. It includes a two-stage qualitative synthesis of 53 (then 16) studies where speech and language therapists explained the work of their practice in depth, and a primary qualitative study focused on one professional jurisdiction, children with speech sound difficulties (SSD). Forty two speech and language therapists from three NHS areas and independent practice in Scotland participated in individual interviews or self-organised pairs or focus groups to discuss in depth how and why they had changed their practice with these children. A variety of comparative methods were used to detail, understand and explain this particular aspect of the social world. The resulting theory of SSD practice change comprises six configured cases of practice change (Transforming; Redistributing; Venturing; Personalising; Delegating; Refining) emerging from an evolving and modifiable practice context. The work that had happened across four key aspects of this context (Intervention; Candidacy; Caseload; Service) explained what made each case possible, and how practice had come to be one way rather than another. Among its practical applications, the theory could help services plan more realistic practice change. In addition, the inductively developed layered model of SSD intervention change has the potential to contribute to speech and language therapy education as well as methodological discussions around complex interventions.

Submitted by Johnny Rodrigues (johnnyrodrigues@ufcg.edu.br) on 2018-08-17T14:06:04Z No. of bitstreams: 1 JOÃO VIVLIAN DE MORAES LIMA MARINUS - DISSERTAÇÃO PPGCC 2010..pdf: 2343869 bytes, checksum: 46e0a7984b1b956fbea2bfcba9e1f631 (MD5) / Made available in DSpace on 2018-08-17T14:06:04Z (GMT). No. of bitstreams: 1 JOÃO VIVLIAN DE MORAES LIMA MARINUS - DISSERTAÇÃO PPGCC 2010..pdf: 2343869 bytes, checksum: 46e0a7984b1b956fbea2bfcba9e1f631 (MD5) Previous issue date: 2010-11-29 / Nos últimos anos, várias pesquisas na área de processamento digital de voz estão sendo feitas, no sentido de criar técnicas que auxiliem o diagnóstico preciso por um especialista de patologias do trato vocal de maneira não invasiva, fazendo com que o paciente se sinta confortável na hora do exame. Este trabalho trata da investigação de técnicas para a classificação de vozes afetadas por patologias da laringe, em especial edema de Reinke, visando a construção de um sistema de apoio ao especialista. O sistema de auxílio ao diagnóstico de patologias da laringe, proposto nesta dissertação, é constituido de 3 etapas principais: pré-processamento do sinal de voz, extração de características e classificação. A etapa de pré-processamento consiste na aquisição do sinal de voz, na aplicação de um filtro de pré ênfase para a minimização dos efeitos da radiação dos lábios e da variação da área da glote, seguido da segmentação e janelamento do sinal. Também foi investigada a não utilização da pré-ênfase nessa etapa. Na fase de extração de características, são utilizados coeficientes obtidos a partir da análise por predição linear (coeficientes LPC), coeficientes cepstrais, coeficientes delta-cepstrais e um vetor de características combinando coeficientes LPC e coeficientes cepstrais. A etapa de classificação é dividida em duas partes: classificação entre voz normal e voz afetada por patologia, sem especificar qual patologia, e caso o sinal seja classificado como voz afetada por patologia, tem-se uma segunda parte, a qual é realizada a classificação entre voz afetada por edema de Reinke e voz afetada por outra patologia. Para as duas partes, foram testados 3 diferentes classificadores: Redes Neurais Multilayer Perceptron - MLP, Modelos de Misturas de Gaussianas e Quantização Vetorial. Para diferenciar entre voz normal e voz afetada por patologia, os melhores resultados foram obtidos utilizando Redes Neurais. Para diferenciar entre voz afetada por edema e voz afetada por outra patologia, os melhores resultados foram obtidos utilizando Quantização Vetorial. Em ambos os casos, os melhores resultados foram obtidos ao se utilizar coeficientes cepstrais e sem utilização da pré-ênfase. / In recent years, several studies in digital voice processing are being made in order to create techniques to support a noninvasive accurate diagnosis of vocal tract diseases by aspecialist, making the patient feel comfortable during examination. This work deals with the investigation of techniques for classification of voices affected by laryngeal pathologies, especially Reinke’s edema, aiming to build a support system to the specialist. The system for the diagnosis of laryngeal pathologies, proposed here, consists of three main steps: preprocessing the speech signal, feature extraction and classification. Preprocessing corresponds the acquisition of voice signal, the application of a pre-emphasis filter for minimizing the radiation effects from the lips and from variation in glottal area, and the signal segmentation and windowing. The non-use of pre-emphasis was also investigated at this point. In the feature extraction step, we use coefficients obtained from the linear prediction analysis (LPC coefficients), cepstral coefficients, delta-cepstral coefficients, and afeature vectorc ombining LPC and cepstral coefficients. The classification is divided into two parts: classification of normal voice versus voice affected by pathology, without specifying which pathology, and if the signal is classified as voice affected by pathology, second part happens, which is performed by the classification between voice affected by Reinke’s edema and voice affected by other pathology. For both parties, 3 different classifiers were tested: Neural Networks Multilayer Perceptron - MLP, Gaussian Mixture Models and Vector Quantization. To differentiate between normal voice and voice affected by pathology, the best results were obtained using Neural Networks. To differentiate between voice affected by edema and voice affected by pathology, the best results were obtained using vector quantization. In both cases, the best results were obtained when usingcepstral coefficients and withoutuse of pre-emphasis.

The goal of my diploma thesis is introduce one of alternative direction {--} music therapy, to outline the sphere of specific learning and behavior disorders, and also to give a guide, how to apply components of music therapy during the work with children with these disorders. The thesis consists of two parts {--} a theoretical and practical part. The theoretical part focuses on defining key terms, such as music therapy, dyslexia, dysgraphia, dysortographia, dyscalculia, dyspinxia, dysmusia, dyspraxia. In my work I aim to clarify the question of ADHD and try to point out the relation of particular learning and behavior disorders. The practical part includes twenty activities that were made firstly according to a methodical manual written by M. Beníčková and Z. Vilímek, who use the Czech method of music therapy {--} Music of body, and secondly on the base of casuistry of two boys attending special practical school. Each activitiy should develop particular skills, comprises tools, motivation, its own description and analysis coming out of a practical accomplishment. The method of observing was used for the evaluation.

Submitted by Johnny Rodrigues (johnnyrodrigues@ufcg.edu.br) on 2018-08-03T19:45:39Z No. of bitstreams: 1 HIDELGARD PAULINO BARBOSA - DISSERTAÇÃO PPGCC 2013..pdf: 11966764 bytes, checksum: 077a69b5088eea2f7109e71871f4e57d (MD5) / Made available in DSpace on 2018-08-03T19:45:39Z (GMT). No. of bitstreams: 1 HIDELGARD PAULINO BARBOSA - DISSERTAÇÃO PPGCC 2013..pdf: 11966764 bytes, checksum: 077a69b5088eea2f7109e71871f4e57d (MD5) Previous issue date: 2013-08 / A voz é o meio de comunicação mais utilizado pelo ser humano. Porém, o sistema fonador humano é suscetível a diversos tipos de patologias que podem prejudicar a produção da voz e, consequentemente, a comunicação. Alguns tipos de exames têm sido utilizados para detectar estas patologias. Porém, eles apresentam desvantagens referentes à acurácia e ao conforto do paciente durante a aplicação, que podem desestimular a busca por tratamento. Por essa razão, técnicas computacionais têm sido empregadas com o intuito de detectar de modo confortável e preciso a presença e o tipo de patologia apresentada pelo sistema fonador. No entanto, os resultados obtidos ainda não possibilitam sua aplicação nas clínicas, principalmente pelo fato de ainda ser considerado um número reduzido de patologias. Visando a contornar esse problema, esta pesquisa propõe uma abordagem fundamentada em um método ainda não utilizado neste contexto: a Predição por Casamento Parcial (Prediction by Partial Matching - PPM), concebida originalmente com fins à compressão de dados. O modelo criado e mantido a partir deste método é alimentado com características acústicas, temporais e estatísticas extraídas dos sinais de voz e permite sua classificação no que se refere à identificação da presença e do tipo de patologia a um baixo custo computacional (velocidade e recursos de armazenamento). Foram obtidos resultados satisfatórios no tocante à presença de patologias. Quanto à discriminação de patologias, os resultados sugerem um potencial do método, embora a sua aplicação ainda necessite de investigações mais aprofundadas / Voice is the most widely used means of communication of mankind. However, speech organs are susceptible to several sort of pathologies, which may harm voice production and, therefore, communication. Several techniques have been used to detect these pathologies. However, they present drawbacks related to accuracy and comfort of patients during the application, which may discourage search for treatment. Thence, computational techniques have been used in order to detect the presence and type of speech pathology comfortably and accurately. But, results are still not good enough for its application in clinics, due to the fact it is considered a small number of distinct pathologies. Aiming to solve this problem, this research proposes using a method not previously employed in classification of vocal tract diseases: Prediction by Partial Matching (PPM), originally conceived for data compression purposes. The PPM model is fed with acoustical, temporal, and statistical features, ali of them extracted from voice signals. This method allowed a satisfactory classification, concerning presence and type of pathology while requiring a low computational cost (speed and storage resources). It were obtained satisfactory results regarding presence of speech pathologies. With regard to pathologies discrimination, the results suggest that this is a highly promising technique, although its application still needs deeper investigations.