Ljudigenkänning möjliggörs genom spektralanalys, som beräknas av den snabba fouriertransformen (FFT), och har under senare år nått stora genombrott i samband med ökningen av datorprestanda och artificiell intelligens. Tekniken är nu allmänt förekommande, i synnerhet inom bioakustik för identifiering av djurarter, en viktig del av miljöövervakning. Det är fortfarande ett växande vetenskapsområde och särskilt igenkänning av fågelsång som återstår som en svårlöst utmaning. Även de främsta algoritmer i området är långt ifrån felfria. I detta kandidatexamensarbete implementerades och utvärderades enkla algoritmer för att para ihop ljud med en ljuddatabas. En filtreringsmetod utvecklades för att urskilja de karaktäristiska frekvenserna vid fem tidsramar som utgjorde basen för jämförelsen och proceduren för ihopparning. Ljuden som användes var förinspelad fågelsång (koltrast, näktergal, kråka och fiskmås) så väl som egeninspelad mänsklig röst (4 unga svenska män). Våra resultat visar att framgångsgraden normalt är 50–70%, den lägsta var fiskmåsen med 30% för en liten databas och den högsta var koltrasten med 90% för en stor databas. Rösterna var svårare för algoritmen att särskilja, men de hade överlag framgångsgrader mellan 50% och 80%. Dock gav en ökning av databasstorleken generellt inte en ökning av framgångsgraden. Sammanfattningsvis visar detta kandidatexamensarbete konceptbeviset bakom fågelsångigenkänning och illustrerar såväl styrkorna som bristerna av dessa enkla algoritmer som har utvecklats. Algoritmerna gav högre framgångsgrad än slumpen (25%) men det finns ändå utrymme för förbättring eftersom algoritmen vilseleddes av ljud av samma frekvenser. Ytterligare studier behövs för att bedöma den utvecklade algoritmens förmåga att identifiera ännu fler fåglar och röster. / Sound recognition is made possible through spectral analysis, computed by the fast Fourier transform (FFT), and has in recent years made major breakthroughs along with the rise of computational power and artificial intelligence. The technology is now used ubiquitously and in particular in the field of bioacoustics for identification of animal species, an important task for wildlife monitoring. It is still a growing field of science and especially the recognition of bird song which remains a hard-solved challenge. Even state-of-the-art algorithms are far from error-free. In this thesis, simple algorithms to match sounds to a sound database were implemented and assessed. A filtering method was developed to pick out characteristic frequencies at five time frames which were the basis for comparison and the matching procedure. The sounds used were pre-recorded bird songs (blackbird, nightingale, crow and seagull) as well as human voices (4 young Swedish males) that we recorded. Our findings show success rates typically at 50–70%, the lowest being the seagull of 30% for a small database and the highest being the blackbird at 90% for a large database. The voices were more difficult for the algorithms to distinguish, but they still had an overall success rate between 50% and 80%. Furthermore, increasing the database size did not improve success rates in general. In conclusion, this thesis shows the proof of concept and illustrates both the strengths as well as short-comings of the simple algorithms developed. The algorithms gave better success rates than pure chance of 25% but there is room for improvement since the algorithms were easily misled by sounds of the same frequencies. Further research will be needed to assess the devised algorithms' ability to identify even more birds and voices.

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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.