Rozprawy doktorskie na temat „Voice biometrics”
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Pillay, Surosh Govindasamy. "Voice biometrics under mismatched noise conditions". Thesis, University of Hertfordshire, 2011. http://hdl.handle.net/2299/5531.
Pełny tekst źródłaFortuna, JoseÌ. "Speaker indexing based on voice biometrics". Thesis, University of Hertfordshire, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.427534.
Pełny tekst źródłaRouse, Kenneth Arthur Gilbert Juan E. "Classifying speakers using voice biometrics In a multimodal world". Auburn, Ala, 2009. http://hdl.handle.net/10415/1824.
Pełny tekst źródłaFirc, Anton. "Použitelnost Deepfakes v oblasti kybernetické bezpečnosti". Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2021. http://www.nusl.cz/ntk/nusl-445534.
Pełny tekst źródłaSanderson, Conrad, i conradsand@ieee org. "Automatic Person Verification Using Speech and Face Information". Griffith University. School of Microelectronic Engineering, 2003. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20030422.105519.
Pełny tekst źródłaSanderson, Conrad. "Automatic Person Verification Using Speech and Face Information". Thesis, Griffith University, 2003. http://hdl.handle.net/10072/367191.
Pełny tekst źródłaThesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Microelectronic Engineering
Full Text
Fransson, Linda, i Therese Jeansson. "Biometric methods and mobile access control". Thesis, Blekinge Tekniska Högskola, Avdelningen för programvarusystem, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-5023.
Pełny tekst źródłaVálková, Jana. "Formy zadávání a zpracování textových dat a informací v podnikových IS - trendy a aktuální praxe". Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-114263.
Pełny tekst źródłaAtah, Alewo Joshua. "Strategies for template-free direct biometric encryption using voice based features". Thesis, University of Kent, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.544079.
Pełny tekst źródłaPatino, Villar José María. "Efficient speaker diarization and low-latency speaker spotting". Thesis, Sorbonne université, 2019. http://www.theses.fr/2019SORUS003/document.
Pełny tekst źródłaSpeaker diarization (SD) involves the detection of speakers within an audio stream and the intervals during which each speaker is active, i.e. the determination of ‘who spoken when’. The first part of the work presented in this thesis exploits an approach to speaker modelling involving binary keys (BKs) as a solution to SD. BK modelling is efficient and operates without external training data, as it operates using test data alone. The presented contributions include the extraction of BKs based on multi-resolution spectral analysis, the explicit detection of speaker changes using BKs, as well as SD fusion techniques that combine the benefits of both BK and deep learning based solutions. The SD task is closely linked to that of speaker recognition or detection, which involves the comparison of two speech segments and the determination of whether or not they were uttered by the same speaker. Even if many practical applications require their combination, the two tasks are traditionally tackled independently from each other. The second part of this thesis considers an application where SD and speaker recognition solutions are brought together. The new task, coined low latency speaker spotting (LLSS), involves the rapid detection of known speakers within multi-speaker audio streams. It involves the re-thinking of online diarization and the manner by which diarization and detection sub-systems should best be combined
Cesario, Lisa. "Progettazione e implementazione di un sistema di autorizzazione elettronico per il trasporto auto di persone disabili con validazione biometrica". Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amslaurea.unibo.it/9684/.
Pełny tekst źródłaPatino, Villar José María. "Efficient speaker diarization and low-latency speaker spotting". Electronic Thesis or Diss., Sorbonne université, 2019. http://www.theses.fr/2019SORUS003.
Pełny tekst źródłaSpeaker diarization (SD) involves the detection of speakers within an audio stream and the intervals during which each speaker is active, i.e. the determination of ‘who spoken when’. The first part of the work presented in this thesis exploits an approach to speaker modelling involving binary keys (BKs) as a solution to SD. BK modelling is efficient and operates without external training data, as it operates using test data alone. The presented contributions include the extraction of BKs based on multi-resolution spectral analysis, the explicit detection of speaker changes using BKs, as well as SD fusion techniques that combine the benefits of both BK and deep learning based solutions. The SD task is closely linked to that of speaker recognition or detection, which involves the comparison of two speech segments and the determination of whether or not they were uttered by the same speaker. Even if many practical applications require their combination, the two tasks are traditionally tackled independently from each other. The second part of this thesis considers an application where SD and speaker recognition solutions are brought together. The new task, coined low latency speaker spotting (LLSS), involves the rapid detection of known speakers within multi-speaker audio streams. It involves the re-thinking of online diarization and the manner by which diarization and detection sub-systems should best be combined
Assaad, Firas Souhail. "Biometric Multi-modal User Authentication System based on Ensemble Classifier". University of Toledo / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1418074931.
Pełny tekst źródłaMekyska, Jiří. "Identifikace osob pomocí otisku hlasu". Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2010. http://www.nusl.cz/ntk/nusl-218235.
Pełny tekst źródłaТодорів, Андрій Дмитрович. "Система багатофакторної аутентифікації користувачів комп’ютерних систем". Master's thesis, КПІ ім. Ігоря Сікорського, 2020. https://ela.kpi.ua/handle/123456789/38366.
Pełny tekst źródłaTopic relevance The solution to the problem of corporate data protection in the XXI century has gone beyond the physical interaction with employees, due to the transition of the required information into a computer format. This feature has formed the need to develop and implement new mechanisms for corporate data protection. The proposed system of authentication of computer system users, developed on the basis of neural network technologies, provides the possibility of user identification on the basis of individual anthropometric visual and voice indicators of the subject, in order to prevent theft of corporate data and identification of criminal entities. The object of study is the transformation of anthropometric indicators into a computer form. The subject of study is the mechanisms of pattern recognition. The goal of this work is to improve the capabilities of biometric identification methods of subjects by developing a new architecture based on neural networks. Study methods. Comparison of existing algorithms on the criteria of accuracy, speed, resource costs, reliability, in order to implement and further modify the corporate control system. The scientific novelty is the development of a new mechanism for identifying subjects that combines algorithms for voice and visual identification of subjects. The practical value lies in the possibility of using this system in a corporate environment in order to prevent data leakage and identification of criminal entities. Low resource consumption contributes to the application of the developed algorithm in highly loaded systems. Structure and scope of work. The master's dissertation consists of an introduction, four chapters, conclusions and appendices. The introduction analyzes the problem of corporate data protection. The prospects of using the mechanisms of biometric voice and visual identification of subjects for its solution are substantiated. Biometric identification algorithms are investigated. The first section describes the existing algorithms for recognizing visual and voice images. The second section investigates the feasibility of using existing algorithms for voice and visual biometric identification, analyzes and compares existing image recognition architectures. The third section describes the process of developing algorithms for visual and voice biometric user identification The fourth section presents the characteristics of the developed COP, the test results, the system is studied on different data sets, and its modification in order to achieve the specified accuracy. The conclusions summarize the results of research and development.
Jeevan, M. "Behavioual biometrics based personal authentication: gait and voice". Thesis, 2017. http://localhost:8080/xmlui/handle/12345678/7402.
Pełny tekst źródłaHenderson, Paul Martin. "Voiceprint Vault : voice authentication service". 2013. http://hdl.handle.net/2152/22603.
Pełny tekst źródłatext
Guedes, Alexandra Patrícia Lopes Pacheco. "Depressão materna na gravidez : efeitos no desenvolvimento fetal e neonatal". Doctoral thesis, 2012. http://hdl.handle.net/1822/21008.
Pełny tekst źródłaConcetualização: A Psicopatologia do Desenvolvimento trouxe uma nova perspetiva na compreensão de como a depressão materna na gravidez pode contribuir para os resultados adversos no desenvolvimento fetal e neonatal. O estudo dos mecanismos subjacentes à transmissão do risco mãe-filho revelou a contribuição de variáveis fetais na explicação das diferenças individuais no desenvolvimento. Objetivos: 1) Estudar os efeitos da depressão materna na gravidez no desenvolvimento fetal e neonatal; 2) Analisar a depressão materna no parto como potencial mediador/moderador da relação entre depressão materna na gravidez e desenvolvimento neonatal; 3) Avaliar a resposta cardíaca fetal à administração de um paradigma de familiaridade-novidade com estímulos auditivos/discursivos; e, 4) Identificar potenciais mecanismos que permitam explicar a relação entre depressão materna na gravidez e desenvolvimento neonatal. Método: Uma amostra de 110 grávidas (no terceiro trimestre de gravidez) foi dividida em dois grupos de acordo com a sua cotação na Edinburgh Postnatal Depression Scale (EPDS: 10, deprimidas; < 10, não-deprimidas). Entre a 33ª e a 37ª semana de gravidez, as participantes contaram uma curta história aos seus fetos, todos os dias. A frequência cardíaca fetal (FCF) foi avaliada à 37ª semana de gestação através de um cardiotocograma computorizado, enquanto uma gravação dos estímulos discursivos (história familiar e história nova) era apresentada próximo do abdómen materno. Medidas da FCF em resposta à estimulação e da biometria fetal foram recolhidas no terceiro trimestre de gestação. Nos primeiros 5 dias após o parto, os recém-nascidos foram avaliados através da Neonatal Behavioral Assessment Scale (NBAS) e do paradigma da ‘Preferencia e habituação pela face/voz da mãe/estranha’; as mães preencheram o EPDS. Resultados: Os fetos de grávidas deprimidas, apresentaram menor perímetro cefálico e abdominal, em comparação com os fetos de grávidas não deprimidas. Recém-nascidos de mães deprimidas, comparativamente com recémnascidos de mães não deprimidas na gravidez, revelaram piores resultados nas subescalas da NBAS (regulação do estado, mudança de estado e habituação); não mostraram preferência visual/auditória pela face/voz da mãe; necessitaram mais apresentações do estímulo face/voz da mãe até se habituarem; e apresentaram maior preferência visual/auditória pela face/voz da estranha após habituação. A depressão no parto não contribuiu para os efeitos da depressão materna na gravidez no desenvolvimento neonatal. Uma maior variabilidade da FCF foi observada durante a apresentação de estímulos discursivos (em oposição ao préteste), bem como na primeira apresentação do estímulo familiar (em oposição ao estímulo novo) e na terceira apresentação do estímulo novo (em oposição à primeira apresentação). Não se observaram diferenças significativas na linha de base da FCF. A variabilidade da FCF mediou a relação entre depressão materna na gravidez e o neurocomportamento do recém-nascido, explicando 11.7% da variância observada. Conclusão: A depressão materna na gravidez é uma condição de risco para o desenvolvimento neonatal, sendo que a sintomatologia depressiva materna nos primeiros dias após o parto não explica os resultados desenvolvimentais do recém-nascido. A variabilidade de FCF surge a explicar a relação entre depressão materna no terceiro trimestre de gestação e desenvolvimento neonatal. Com vista à redução do risco associado à depressão materna justifica-se a implementação de medidas preventivas de saúde materno-fetal, precocemente na gravidez.
Background: Developmental Psychopathology has brought new possibilities for understanding how maternal depression during pregnancy may contribute to adverse foetal and neonatal development. The study of the underlying mechanisms of motherto- child transmission of risk, have shown the contribution of foetal variables in the explanation of the following development. Aims: 1) To study the effect of mother’s depression during pregnancy on foetal and neonatal development; 2) To analyse mother’s depression at childbirth as a potential mecanism in the explanation of the relationship between mother’s depression during pregnancy and neonate development; 3) To evaluate the fetal cardiac response during the administration of a familiaritynovelty paradigm with auditory/discursive stimuli; and 4) To identify potential foetal mediators/moderators of the relationship between mother’s depression during pregnancy and neonatal development. Method: A sample of 110 pregnant women (at the third trimester of pregnancy) was divided in 2 groups according to their scores on the Edinburgh Postnatal Depression Scale (EPDS: 10, depressed; < 10, nondepressed). Between the 33rd and the 37th week of gestation, mothers recited a short nursery rhyme to their fetuses every day. Fetal heart rate (FHR) was assessed at 37 weeks gestation by computerised cardiotocography, while pre-recorded speech stimuli (familiar and novel nursery rhymes) were presented using a loudspeaker held above the maternal abdomen. Measures of FHR in response to stimuli and foetal biometry were collected at the third pregnancy trimester. In the first 5 days after birth, neonatal performance on the Neonatal Behavioral Assessment Scale (NBAS) and in the ‘Preference and habituation to the mother’s face/voice versus stranger’ paradigm was assessed; each mother filled out an EPDS. Results: The foetuses of depressed pregnant women, had an inferior head and abdomen circumference growth, compared to foetuses of non-depressed pregnant women. Neonates of depressed mothers, compared to neonates of non-depressed mothers, achieved lower scores on the NBAS scales (regulation of state, range of state, and habituation); did not show a visual/auditory preference for the mother’s face/voice; required more trials to become habituated; and showed a higher visual/auditory preference for the stranger’s face/voice after habituation. Depression at childbirth does not contribute to the effect of antenatal depression on neonatal development. A significantly higher FHR variability was observed during stimuli presentation (in opposition to pretest), as well as during the first presentation of the familiar stimulus (in opposition to the novel stimulus), and in the third presentation of the novel stimulus (in opposition to its first presentation). No significant changes were observed in baseline FHR. FHR variability mediates the relationship between mother’s depression during pregnancy and neonate neurobehaviour, explaining 11.7% of the variance observed. Conclusion: Mother’s depression during pregnancy is a risk condition for neonates’ development. Depression at the first days after childbirth does not contribute to neonates’ developmental outcomes. FHR variability explaine the relation between mother’s depression at the third pregnancy trimester and neonatal development. In order to reduce the risk associated with maternal depression, the implementation of preventive maternal-fetal health measures, early in pregnancy, is needed.
Макар, Степан Михайлович, i Stepan Makar. "Обгрунтування методу ідентифікації особи в телекомунікаційній мережі". Master's thesis, 2019. http://elartu.tntu.edu.ua/handle/lib/29818.
Pełny tekst źródłaThe master's thesis is devoted to solving the actual scientific and practical problem of developing methods of providing information and functional security of wireless infrastructure on the basis of hardware separation of subscribers to increase the level of its protection against security threats of various nature, which consist in the developed theoretical bases, methods, models and tools wireless systems and networks.
ВСТУП 10 РОЗДІЛ 1 ВИБІР НАПРЯМКУ ТА ТЕМИ НАУКОВОГО ДОСЛІДЖЕННЯ 14 1.1 Завдання ідентифікації та аутентифікації користувача 14 1.2 Актуальні способи ідентифікації особи 23 1.3 Основні засади роботи систем біометричної ідентифікації 37 1.4 Описовий аналіз проблематики голосової ідентифікації 43 1.5 Висновки до розділу 1 46 РОЗДІЛ 2 МЕТОДОЛОГІЇ ОБРОБКИ ГОЛОСОВИХ СИГНАЛІВ ДЛЯ ЗАДАЧІ ІДЕНТИФІКАЦІЇ ОСОБИ 47 2.1 Завдання ідентифікації особи 47 2.2. Аналіз процедури утворення голосового сигналу та моделей процесу породження голосу 48 2.3 Основні вимоги до методології обробки аудіо сигналів для задачі голосової ідентифікації особи 56 2.4 Метод дослідження голосового сигналу з метою ідентифікації користувача 58 2.5 Висновки до розділу 2 62 РОЗДІЛ 3 ЕКСПЕРИМЕНТ З ВІДБОРУ ГОЛОСОВИХ СИГНАЛІВ 63 3.1 Обгрунтування структури експерименту з відбору голосових сигналів 63 3.2 Обгрунтування відбору параметрів мікрофона 64 3.3 Обгрунтування відбору параметрів АЦП у звуковій карті 65 3.4 Висновки розділу 3 67 РОЗДІЛ 4 ОБРОБКА ГОЛОСОВИХ СИГНАЛІВ З МЕТОЮ ІДЕНТИФІКАЦІЇ ОСОБИ 68 4.1 Визначення частотних параметрів формант голосових сигналів 68 4.2 Обчислення значень періоду основного тону голосових сигналів 70 4.3 Висновки до розділу 4 75 РОЗДІЛ 5 СПЕЦАЛЬНА ЧАСТИНА 77 5.1 Метрологічне забезпечення наукового дослідженя 77 5.2 Побудова прикладного програмного забезпечення для розв’язування наукової задачі 78 РОЗДІЛ 6 ОБҐРУНТУВАННЯ ЕКОНОМІЧНОЇ ЕФЕКТИВНОСТІ 85 6.1. Визначення стадій технологічного процесу та загальної тривалості проведення науково-дослідних робіт 85 6.2. Визначення витрат на оплату праці та відрахувань на соціальні заходи 88 6.3. Розрахунок витрат на електроенергію 92 6.4 Розрахунок витрат на матеріали 92 6.5 Розрахунок суми амортизаційних відрахувань 93 6.6 Обчислення накладних витрат 94 6.7 Складання кошторису витрат та визначення собівартості науково-дослідних робіт 95 6.8 Розрахунок ціни науково-дослідних робіт 96 6.9 Визначення економічної ефективності і терміну окупності капітальних вкладень 96 6.10 Висновок до розділу 6 98 РОЗДІЛ 7 ОХОРОНА ПРАЦІ ТА БЕЗПЕКА В НАДЗВИЧАЙНИХ СИТУАЦІЯХ 99 7.1 Охорона праці 99 7.2 Безпека в надзвичайних ситуаціях 110 РОЗДІЛ 8 ЕКОЛОГІЯ 114 8.1 Електромагнітне забруднення довкілля, його вплив на людину, шляхи його зменшення 114 8.2 Джерела шуму і вібрацій, методи їх знешкодження 116 ВИСНОВКИ 120 СПИСОК ВИКОРИСТАНИХ ДЖЕРЕЛ 122