No description available.

This research is devoted to the development of the student payment system (SPS) - a complex project implemented by a group of students of the Ural Federal University. The purpose of SPS is to manage students' finances, allowing them to send and receive money without commission and offering favorable exchange rates. The key goal of this project is to minimize operating costs by using artificial intelligence to support customers within the platform. The proposed SPS web application integrates three critical models to ensure security and effective customer support: 1. Facial recognition model: This model improves security by verifying the user's identity based on facial features, ensuring that only authorized users can access their accounts. 2. Voice Recognition Model: Adding another layer of security, this model verifies users based on voice data, providing a strong authentication method. 3. Natural Language Processing (NLP) Model: This model enables seamless interaction between the system and users, offering automated and intelligent customer support. / Данное исследование посвящено разработке студенческой платежной системы (SPS) - комплексного проекта, реализуемого группой студентов Уральского федерального университета. Целью SPS является управление финансами студентов, позволяя им отправлять и получать деньги без комиссии и предлагая выгодные курсы обмена. Ключевая цель этого проекта - минимизировать операционные расходы за счет использования искусственного интеллекта для поддержки клиентов в рамках платформы. Предлагаемое веб-приложение SPS объединяет три критически важные модели для обеспечения безопасности и эффективной поддержки клиентов: 1. Модель распознавания лиц: Эта модель повышает безопасность, проверяя личность пользователя по чертам лица, гарантируя, что только авторизованные пользователи смогут получить доступ к своим учетным записям. 2. Модель распознавания голоса: Добавляя еще один уровень безопасности, эта модель проверяет пользователей на основе голосовых данных, обеспечивая надежный метод аутентификации. 3. Модель обработки естественного языка (NLP): Эта модель обеспечивает беспрепятственное взаимодействие между системой и пользователями, предлагая автоматизированную и интеллектуальную поддержку клиентов.

Die korrekte Wahrnehmung stimmlicher Information ist eine Grundvoraussetzung erfolgreicher zwischenmenschlicher Kommunikation. Die Stimme einer anderen Person liefert Information darüber wer spricht (Sprechererkennung), was gesagt wird (stimmliche Spracherkennung) und über den emotionalen Zustand einer Person (stimmliche Emotionserkennung). Autismus Spektrum Störungen (ASS) sind mit Einschränkungen in der Sprechererkennung und der stimmlichen Emotionserkennung assoziiert, während die Wahrnehmung stimmlicher Sprache relativ intakt ist. Die zugrunde liegenden Mechanismen dieser Einschränkungen sind bisher jedoch unklar. Es ist beispielsweise unklar, auf welcher Verarbeitungsstufe diese Einschränkungen in der Stimmenwahrnehmung entstehen oder ob sie mit einer Dysfunktion stimmensensitiver Hirnregionen in Verbindung stehen. Im Rahmen meiner Dissertation haben wir systematisch Stimmenverarbeitung und dessen Einschränkungen bei Erwachsenen mit hochfunktionalem ASS und typisch entwickelten Kontrollprobanden (vergleichbar in Alter, Geschlecht und intellektuellen Fähigkeiten) untersucht. In den ersten beiden Studien charakterisierten wir Sprechererkennung bei ASS mittels einer umfassenden verhaltensbezogenen Testbatterie und zweier funktionaler Magnet Resonanz Tomographie (fMRT) Experimente. In der dritten Studie untersuchten wir Mechanismen eingeschränkter stimmlicher Emotionserkennung bei ASS. Unsere Ergebnisse bringen neue Kenntnisse für Modelle zwischenmenschlicher Kommunikation und erhöhen unser Verständnis elementarer Mechanismen, die den Kernsymptomen in ASS wie Schwierigkeiten in der Kommunikation, zugrunde liegen könnten. Beispielsweise unterstützen unsere Ergebnisse die Annahme, dass Einschränkungen in der Wahrnehmung und Integration basaler sensorischer Merkmale (i.S. akustischer Merkmale der Stimme) entscheidend zu Einschränkungen in sozialer Kognition (i.S. Sprechererkennung und stimmliche Emotionserkennung) beitragen. / The correct perception of information carried by the voice is a key requirement for successful human communication. Hearing another person’s voice provides information about who is speaking (voice identity), what is said (vocal speech) and the emotional state of a person (vocal emotion). Autism spectrum disorder (ASD) is associated with impaired voice identity and vocal emotion perception while the perception of vocal speech is relatively intact. However, the underlying mechanisms of these voice perception impairments are unclear. For example, it is unclear at which processing stage voice perception difficulties occur, i.e. whether they are rather of apperceptive or associative nature or whether impairments in voice identity processing in ASD are associated with dysfunction of voice-sensitive brain regions. Within the scope of my dissertation we systematically investigated voice perception and its impairments in adults with high-functioning ASD and typically developing matched controls (matched pairwise on age, gender, and intellectual abilities). In the first two studies we characterised the behavioural and neuronal profile of voice identity recognition in ASD using two functional magnetic resonance imaging (fMRI) experiments and a comprehensive behavioural test battery. In the third study we investigated the underlying behavioural mechanisms of impaired vocal emotion recognition in ASD. Our results inform models on human communication and advance our understanding for basic mechanisms which might contribute to core symptoms in ASD, such as difficulties in communication. For example, our results converge to support the view that in ASD difficulties in perceiving and integrating lower-level sensory features, i.e. acoustic characteristics of the voice might critically contribute to difficulties in higher-level social cognition, i.e. voice identity and vocal emotion recognition.

Submitted by Johnny Rodrigues (johnnyrodrigues@ufcg.edu.br) on 2018-07-30T21:22:20Z No. of bitstreams: 1 DANIELLA DIAS CAVALCANTE DA SILVA - TESE PPGEE 2011..pdf: 21267862 bytes, checksum: 34609e6f0c5b3d3d5dbe954562ec3132 (MD5) / Made available in DSpace on 2018-07-30T21:22:20Z (GMT). No. of bitstreams: 1 DANIELLA DIAS CAVALCANTE DA SILVA - TESE PPGEE 2011..pdf: 21267862 bytes, checksum: 34609e6f0c5b3d3d5dbe954562ec3132 (MD5) Previous issue date: 2011-12 / Com o advento da tecnologia, as máquinas predominam em quase todos os cenários do cotidiano das pessoas, sejam essas máquinas computadores, eletrodomésticos, dispositivos portáteis, etc. Com isso, nada melhor do que dotá-las com a capacidade de percepção e compreensão da voz humana, que é a forma mais simples, natural e eficaz do ser humano expressar seus pensamentos. Apesar de muitas pesquisas na área de Processamento Digital de Sinais de Voz (PDSV) terem permitido o desenvolvimento de sistemas de Reconhecimento de Faia bastante eficientes, requisitos de processamento ainda dificultam a implementação desses sistemas em dispositivos com pequeno poder computacional, como celulares, palmtops e eíetrodomésticos. Para permitir a implementação de sistemas de Reconhecimento de Faia nesse contexto, alguns trabalhos sacrificam a eficiência no processo de reconhecimento em nome da redução do tamanho físico e de exigências computacionais. Assim, a busca por modelagens acústicas e linguísticas othnizadas, associadas ao uso de bases de dados representativas, pode levar a ura compromisso entre desempenho do sistema em termos de taxas de reconhecimento e exigências computacionais impostas por sistemas embarcados. O objetivo principal deste trabalho consiste na modelagem da arquitetura de um sistema de reconhecimento de fala contínua para o português brasileiro, utilizando Modelos Ocultos de Markov, de forma a possibilitar sua implementação em um sistema embarcado com recursos computacionais limitados. A fim de selecionar a configuração que melhor atenda esse objetivo, foram realizados experimentos e análises, de modo a identificar possíveis adaptações, a partir de simplificações matemáticas e redução de parâmetros nas etapas do processo de reconhecimento. Em todo lho, foi considerada a relação entre a taxa de reconhecimento e o custo computacional. A arquitetura do sistema embarcado desenvolvida e o seu processo de modelagem, incluindo os experimentos, as análises e os seus respectivos resultados, serão apresentados e discutidos no decorrer deste documento. / WIth the advent of technology, machines predominate in aímost ali seenarios of everyday life. The possibiiity of performing human-maehine comniunication through speech makes this interact.ion easier and more productive. However, processing requirements still difficult tlíe implementation oF systems for automatic continuous speech recognition on devices with low computational power sucJi as mobile phones, palmtops and appliances. To allow the implementation of speech recognition systems in this context. some works sacrifice efficiency in the recognition process for redueing the chip area and computational requirements. For this purpose, it becomes necessary to research for optimized acoustic and language modeling, associated with use of representative databases, looking for a good compromise between recognitioa vaies and compuiational demands imposed by embedded systems. The main goai of this work is to model the architecture of a system for continuous speech recognition Brazilian Portuguese, in order to enable its implementation in an embedded system with limited computtng resources. In order to select the setting that best nieets this goal, experiments and analysis were performed. The purpose of these was to identify possible adaptations, from mathematical simpiifícations and reduction of parameters in the steps of the recognition process. During the deveiopinent of this work, the relationship between recognition rate and computational cost was considered. The embedded system architecture developed and its modeling process, including experiments. analysis and their results will be presented and díscussed thxoughout this document.

Detta arbete har utforskat interaktionen mellan människa och automation inom det avhjälpande underhållet på två tillverkande företag. Arbetets syfte är bidra till att människor och automationsutrustningar framgångsrikt kan samarbeta i framtidens fabriker. Studien har undersökt hur interaktionen ser ut i dagsläget, var det idag saknas interaktion, hur interaktionen kan komma att se ut i framtiden samt vilka krav som behöver uppnås för att komma dit. Studien har också haft ett fokus på hållbar utveckling och hur interaktionen kan påverka denna. Projektets resultat är framtaget genom att utföra två deltagande observationer, en på vartdera företaget samt fyra semistrukturerade intervjuer per företag. I dagsläget sker mycket kommunikation genom telefon för att påkalla uppmärksamhet hos personal med information om larm och plats. Felsökning sker genom en panel vid maskinen alternativt via dator som kopplas upp mot maskinen vid djupare felsökning. Det finns i dagsläget även teknik såsom kommunikationsradio, tangentbord och mus som undviks att användas i största möjliga mån eftersom de anses vara svåra att manövrera. Resultaten visar att det finns ett behov av att få mer information i underhållets alla faser och att tekniken som används behöver vara mer mobil än i dagsläget. Författarna ger förslag på att handhållna enheter kan användas i framtidens underhåll och att röstigenkänning, Virtual Reality och Augmented Reality kan användas i dessa. Även smarta klockor rekommenderas att användas för att påkalla uppmärksamhet hos personal och samtidigt ge information om larm. Det finns en förhoppning om att mer information och mer mobil teknik kan effektivisera underhållet och därmed minska tiden för att utföra ett avhjälpande underhåll. Författarna rekommenderar starkt att all teknik som är tänkt att bli implementerad först testas i en realistisk miljö av de personer som ska använda tekniken. / The project has explored the interaction between humans and automation within the remedial maintenance on two manufacturing companies. The purpose of the project is to contribute to the interaction between humans and automation and by that make it successful in the future. The study has investigated how the present interaction is designed, where there is a need for interaction, how the interaction can be designed in the future together with the requirements that will need to be achieved to get there. In this study there is also a focus on sustainable development and how the interaction affects it. The result of the project is produced by performing two attendance observations, one at each company and four semi-structured interviews at each company. Today a lot of communication is done by phone to get the attention of personnel and summon them to the machine that has stopped. The troubleshooting of the machine is done in a panel or with a computer if deeper troubleshooting is needed. The computer needs to be connected to the machine. Today there are some technics that are present but these are not used due to the fact that they are perceived tedious to use. These technics are communication radio, mouse and keyboard. The result of the study indicates that there is a need for more information in all the phases of a remedial maintenance work. It also shows that the technics needs to be more mobile compared to how it is today. The authors recommends that handheld devices are used in the future and that softwares such as voice recognition, Virtual Reality and Augmented Reality are used within the handheld devices. Smartwatches are also interesting in an attention point of view where alarm messages can be shown. There is a belief that with more information and more mobility the maintenance will be more effective in the future and that the time for remedial maintenance will reduce. The authors strongly recommend that all technics that will be implemented need to first be tested in a realistic environment and by the people that should use it.