Gotowe bibliografie tematyczne / Voice biometrics

Gotowa bibliografia na temat „Voice biometrics”

Autor: Grafiati
Data publikacji: 4 czerwca 2021
Data aktualizacji: 7 września 2024

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Artykuły w czasopismach na temat "Voice biometrics"

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Joshi, Amogh. "Future of Cybersecurity: A Study on Biometric Scans". International Journal for Research in Applied Science and Engineering Technology 9, nr 11 (30.11.2021): 1180–85. http://dx.doi.org/10.22214/ijraset.2021.38913.

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Abstract: Biometrics is a statistical analysis of people's unique behavioral characteristics. The technology is used for CYBERSECURITY. The basics of biometric authentication is that to stop security breaches by analyzing a person’s unique behavioral characteristics. The term biometrics is derived from the Greek word’s “bios” meaning life and “metricos” meaning to measure. It refers to measurements of physical and biological characteristics of the human body. In this paper, we have studied some biometric methods such as facial recognition, iris recognition, Retinal Recognition, voice recognition. Keywords: Biometrics, Cybersecurity, Biometric Scan, Retinal Scan, Iris Scan, Gait, Voice Recognition.
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Markowitz, Judith A. "Voice biometrics". Communications of the ACM 43, nr 9 (wrzesień 2000): 66–73. http://dx.doi.org/10.1145/348941.348995.

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K. P. Ajitha, Gladis, i D. Sharmila. "Systematic digital signal processing approach in various biometric identification". i-manager's Journal on Digital Signal Processing 10, nr 2 (2022): 7. http://dx.doi.org/10.26634/jdp.10.2.19290.

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Biometrics are unique physical characteristics, such as fingerprints, that can be used for automatic recognition. Biometric identifiers are often classified as physiological characteristics associated with body shape. The goal is to capture a piece of biometric data from that person. It could be a photograph of their face, a recording of their voice, or a picture of their fingerprints. While there are numerous types of biometrics for authentication, the six most common are facial, voice, iris, near-field communication, palm or finger vein patterns, and Quick Response (QR) code. Biometrics is a subset of the larger field of human identification science. This paper explores computational approaches to speaker recognition, face recognition, speech recognition, and fingerprint recognition to assess the overall state of digital signal processing in biometrics.
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D S, Dr Dinesh Kumar. "Human Authentication using Face, Voice and Fingerprint Biometrics". International Journal for Research in Applied Science and Engineering Technology 9, nr VII (15.07.2021): 853–62. http://dx.doi.org/10.22214/ijraset.2021.36381.

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Multimodal biometric approaches are growing in importance for personal verification and identification, since they provide better recognition results and hence improve security compared to biometrics based on a single modality. In this project, we present a multimodal biometric system that is based on the fusion of face, voice and fingerprint biometrics. For face recognition, we employ Haar Cascade Algorithm, while minutiae extraction is used for fingerprint recognition and we will be having a stored code word for the voice authentication, if any of these two authentication becomes true, the system consider the person as authorized person. Fusion at matching score level is then applied to enhance recognition performance. In particular, we employ the product rule in our investigation. The final identification is then performed using a nearest neighbour classifier which is fast and effective. Experimental results confirm that our approach achieves excellent recognition performance, and that the fusion approach outperforms biometric identification based on single modalities.
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Sable, Harsh, i Divya Bajpai Tripathy. "A Review on Comparative Analysis on Different Sort of Physiological and Behavioral Biometric Framework". International Journal of Advance Research and Innovation 9, nr 2 (2021): 1–9. http://dx.doi.org/10.51976/ijari.922101.

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Biometrics as the investigation of seeing an individual ward on their physical or conduct characteristics, biometric have now been conveyed in diverse business, ordinary resident and national security applications. Customarily the usage of biometrics devices has improved our capacity to give approved entry to material foundations. Biometric is the usage of a person's novel physiological, lead, and morphological trademark to give valuable person distinguishing proof. Biometric structures that are starting at now available today break down fingerprints, engravings, iris and retina models, and face. Mechanisms that are similar to biometrics anyway are not named such are lead systems, for instance, voice, imprint and keystroke mechanisms. These days biometrics is in effect effectively executed in numerous fields like measurable, security, recognizable proof and approval frameworks.
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Jansen, Fieke, Javier Sánchez-Monedero i Lina Dencik. "Biometric identity systems in law enforcement and the politics of (voice) recognition: The case of SiiP". Big Data & Society 8, nr 2 (lipiec 2021): 205395172110636. http://dx.doi.org/10.1177/20539517211063604.

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Biometric identity systems are now a prominent feature of contemporary law enforcement, including in Europe. Often advanced on the premise of efficiency and accuracy, they have also been the subject of significant controversy. Much attention has focussed on longer-standing biometric data collection, such as finger-printing and facial recognition, foregrounding concerns with the impact such technologies can have on the nature of policing and fundamental human rights. Less researched is the growing use of voice recognition in law enforcement. This paper examines the case of the recent Speaker Identification Integrated Project, a European wide initiative to create the first international and interoperable database of voice biometrics, now the third largest biometric database at Interpol. Drawing on Freedom of Information requests, interviews and public documentation, we outline the emergence and features of SiiP and explore how voice is recognised and attributed meaning. We understand Speaker Identification Integrated Project as constituting a particular ‘regime of recognition’ premised on the use of soft biometrics (age, language, accent and gender) to disembed voice in order to optimise for difference. This, in turn, has implications for the nature and scope of law enforcement, people's position in society, and justice concerns more broadly.
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Kumar Singha, Anjani, Anshu Singla i Rajneesh Kumar Pandey. "STUDY AND ANALYSIS ON BIOMETRICS AND FACE RECOGNITION METHODS". EPH - International Journal of Science And Engineering 2, nr 2 (27.06.2016): 29–34. http://dx.doi.org/10.53555/eijse.v2i2.145.

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Human Biometrics is a rising technology, which has been broadly used in forensics, safe access and top-security prison. A biometric system is primarily a pattern recognition system that recognizes a person by determining the verification by using his different biological features i.e. Fingerprint, retina-scan, iris scan, hand geometry, and face recognition are important physiological biometrics and behavioral trait are Voice recognition, keystroke-scan, and signature-scan. In this paper different biometrics techniques such as Iris scan, retina scan and face recognition techniques are discussed.
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Czyzewski, Andrzej. "Enhancing voice biometric security: Evaluating neural network and human capabilities in detecting cloned voices". Journal of the Acoustical Society of America 155, nr 3_Supplement (1.03.2024): A68. http://dx.doi.org/10.1121/10.0026827.

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This study assesses speaker verification efficacy in detecting cloned voices, particularly in safety-critical applications such as healthcare documentation and banking biometrics. It compares deeply trained neural networks like the Deep Speaker with human listeners in recognizing these cloned voices, underlining the severe implications of voice cloning in these sectors. Cloned voices in healthcare could endanger patient safety by altering medical records, causing inaccurate diagnoses and treatments. In banking, they threaten biometric security, increasing the risk of financial fraud and identity theft. The research reveals the neural network's superiority over human detection in pinpointing cloned voices, underscoring the urgent need for sophisticated AI-based security. The study stresses the importance of developing robust defenses against voice cloning attacks, which can have critical consequences in healthcare and fintech. This research is crucial for enhancing security in areas reliant on voice authentication, safeguarding confidential data, and preserving the integrity of vital services. The Polish National Center for Research and Development (NCBR) initially supported the project “BIOPUAP” (POIR.01.01.01-0092/19), which focused on digital banking. Subsequently, the project “ADMEDVOICE” (INFOSTRATEG4/0003/2022), also supported by the NCBR, conducted further research into voice cloning in the healthcare sector.
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Chinyemba, Melissa K., i Jackson Phiri. "Gaps in the Management and Use of Biometric Data: A Case of Zambian Public and Private Institutions". Zambia ICT Journal 2, nr 1 (29.06.2018): 35–43. http://dx.doi.org/10.33260/zictjournal.v2i1.49.

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The current physical and cybersecurity systems rely on traditional three-factor authentication to mitigate the threats posed by insider attacks. Key is the use of biometric information. Biometrics are a unique measurement and analysis of the unique physiological special traits such as voice, eye structure and others that can be used in the discipline of varying person identification. Biometry, which is the analysis of these biometrics is a complex process but guarantees identification and non-repudiation. If used to identify humans then several issues such as where is the biometric data stored? Who has access to it? And how does one ensure that such data satisfies the principle of availability. To achieve availability, secure transportation arises. To achieve transportation, non-repudiation, confidentiality and authentication, integrity arise. A storage and transport system is recommended to these challenges. In this paper, we explore the gaps into how public and private institution store and manage biometrics information. We benchmarked each organization again the ISO 30107 and ISO 24745. Our results show that while most companies are adopting and using biometrics systems, few have adopted the ISO biometrics standards that govern the storage and management of biometric information and hence creating security risk.
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Salama, Gerges M., Safaa El-Gazar, Basma Omar, Rana M. Nassar, Ashraf A. M. Khalaf, Ghada M. El-banby, Hesham F. A. Hamed, Walid El-shafai i Fathi E. Abd el-samie. "Cancelable biometric system for IoT applications based on optical double random phase encoding". Optics Express 30, nr 21 (28.09.2022): 37816. http://dx.doi.org/10.1364/oe.466101.

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The security issue is essential in the Internet-of-Things (IoT) environment. Biometrics play an important role in securing the emerging IoT devices, especially IoT robots. Biometric identification is an interesting candidate to improve IoT usability and security. To access and control sensitive environments like IoT, passwords are not recommended for high security levels. Biometrics can be used instead, but more protection is needed to store original biometrics away from invaders. This paper presents a cancelable multimodal biometric recognition system based on encryption algorithms and watermarking. Both voice-print and facial images are used as individual biometrics. Double Random Phase Encoding (DRPE) and chaotic Baker map are utilized as encryption algorithms. Verification is performed by estimating the correlation between registered and tested models in their cancelable format. Simulation results give Equal Error Rate (EER) values close to zero and Area under the Receiver Operator Characteristic Curve (AROC) equal to one, which indicates the high performance of the proposed system in addition to the difficulty to invert cancelable templates. Moreover, reusability and diversity of biometric templates is guaranteed.
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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.

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This thesis describes research into effective voice biometrics (speaker recognition) under mismatched noise conditions. Over the last two decades, this class of biometrics has been the subject of considerable research due to its various applications in such areas as telephone banking, remote access control and surveillance. One of the main challenges associated with the deployment of voice biometrics in practice is that of undesired variations in speech characteristics caused by environmental noise. Such variations can in turn lead to a mismatch between the corresponding test and reference material from the same speaker. This is found to adversely affect the performance of speaker recognition in terms of accuracy. To address the above problem, a novel approach is introduced and investigated. The proposed method is based on minimising the noise mismatch between reference speaker models and the given test utterance, and involves a new form of Test-Normalisation (T-Norm) for further enhancing matching scores under the aforementioned adverse operating conditions. Through experimental investigations, based on the two main classes of speaker recognition (i.e. verification/ open-set identification), it is shown that the proposed approach can significantly improve the performance accuracy under mismatched noise conditions. In order to further improve the recognition accuracy in severe mismatch conditions, an approach to enhancing the above stated method is proposed. This, which involves providing a closer adjustment of the reference speaker models to the noise condition in the test utterance, is shown to considerably increase the accuracy in extreme cases of noisy test data. Moreover, to tackle the computational burden associated with the use of the enhanced approach with open-set identification, an efficient algorithm for its realisation in this context is introduced and evaluated. The thesis presents a detailed description of the research undertaken, describes the experimental investigations and provides a thorough analysis of the outcomes.
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Fortuna, José. "Speaker indexing based on voice biometrics". Thesis, University of Hertfordshire, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.427534.

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Rouse, Kenneth Arthur Gilbert Juan E. "Classifying speakers using voice biometrics In a multimodal world". Auburn, Ala, 2009. http://hdl.handle.net/10415/1824.

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Firc, 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.

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Deepfake technológia je v poslednej dobe na vzostupe. Vzniká mnoho techník a nástrojov pre tvorbu deepfake médií a začínajú sa používať ako pre nezákonné tak aj pre prospešné činnosti. Nezákonné použitie vedie k výskumu techník pre detekciu deepfake médií a ich neustálemu zlepšovaniu, takisto ako k potrebe vzdelávať širokú verejnosť o nástrahách, ktoré táto technológia prináša. Jedna z málo preskúmaných oblastí škodlivého použitia je používanie deepfake pre oklamanie systémov hlasovej autentifikácie. Názory spoločnosti na vykonateľnosť takýchto útokov sa líšia, no existuje len málo vedeckých dôkazov. Cieľom tejto práce je preskúmať aktuálnu pripravenosť systémov hlasovej biometrie čeliť deepfake nahrávkam. Vykonané experimenty ukazujú, že systémy hlasovej biometrie sú zraniteľné pomocou deepfake nahrávok. Napriek tomu, že skoro všetky verejne dostupné nástroje a modely sú určené pre syntézu anglického jazyka, v tejto práci ukazujem, že syntéza hlasu v akomkoľvek jazyku nie je veľmi náročná. Nakoniec navrhujem riešenie pre zníženie rizika ktoré deepfake nahrávky predstavujú pre systémy hlasovej biometrie, a to používať overenie hlasu závislé na texte, nakoľko som ukázal, že je odolnejšie proti deepfake nahrávkam.
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Sanderson, 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.

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Identity verification systems are an important part of our every day life. A typical example is the Automatic Teller Machine (ATM) which employs a simple identity verification scheme: the user is asked to enter their secret password after inserting their ATM card; if the password matches the one prescribed to the card, the user is allowed access to their bank account. This scheme suffers from a major drawback: only the validity of the combination of a certain possession (the ATM card) and certain knowledge (the password) is verified. The ATM card can be lost or stolen, and the password can be compromised. Thus new verification methods have emerged, where the password has either been replaced by, or used in addition to, biometrics such as the person’s speech, face image or fingerprints. Apart from the ATM example described above, biometrics can be applied to other areas, such as telephone & internet based banking, airline reservations & check-in, as well as forensic work and law enforcement applications. Biometric systems based on face images and/or speech signals have been shown to be quite effective. However, their performance easily degrades in the presence of a mismatch between training and testing conditions. For speech based systems this is usually in the form of channel distortion and/or ambient noise; for face based systems it can be in the form of a change in the illumination direction. A system which uses more than one biometric at the same time is known as a multi-modal verification system; it is often comprised of several modality experts and a decision stage. Since a multi-modal system uses complimentary discriminative information, lower error rates can be achieved; moreover, such a system can also be more robust, since the contribution of the modality affected by environmental conditions can be decreased. This thesis makes several contributions aimed at increasing the robustness of single- and multi-modal verification systems. Some of the major contributions are listed below. The robustness of a speech based system to ambient noise is increased by using Maximum Auto-Correlation Value (MACV) features, which utilize information from the source part of the speech signal. A new facial feature extraction technique is proposed (termed DCT-mod2), which utilizes polynomial coefficients derived from 2D Discrete Cosine Transform (DCT) coefficients of spatially neighbouring blocks. The DCT-mod2 features are shown to be robust to an illumination direction change as well as being over 80 times quicker to compute than 2D Gabor wavelet derived features. The fragility of Principal Component Analysis (PCA) derived features to an illumination direction change is solved by introducing a pre-processing step utilizing the DCT-mod2 feature extraction. We show that the enhanced PCA technique retains all the positive aspects of traditional PCA (that is, robustness to compression artefacts and white Gaussian noise) while also being robust to the illumination direction change. Several new methods, for use in fusion of speech and face information under noisy conditions, are proposed; these include a weight adjustment procedure, which explicitly measures the quality of the speech signal, and a decision stage comprised of a structurally noise resistant piece-wise linear classifier, which attempts to minimize the effects of noisy conditions via structural constraints on the decision boundary.
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Sanderson, Conrad. "Automatic Person Verification Using Speech and Face Information". Thesis, Griffith University, 2003. http://hdl.handle.net/10072/367191.

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Identity verification systems are an important part of our every day life. A typical example is the Automatic Teller Machine (ATM) which employs a simple identity verification scheme: the user is asked to enter their secret password after inserting their ATM card; if the password matches the one prescribed to the card, the user is allowed access to their bank account. This scheme suffers from a major drawback: only the validity of the combination of a certain possession (the ATM card) and certain knowledge (the password) is verified. The ATM card can be lost or stolen, and the password can be compromised. Thus new verification methods have emerged, where the password has either been replaced by, or used in addition to, biometrics such as the person’s speech, face image or fingerprints. Apart from the ATM example described above, biometrics can be applied to other areas, such as telephone & internet based banking, airline reservations & check-in, as well as forensic work and law enforcement applications. Biometric systems based on face images and/or speech signals have been shown to be quite effective. However, their performance easily degrades in the presence of a mismatch between training and testing conditions. For speech based systems this is usually in the form of channel distortion and/or ambient noise; for face based systems it can be in the form of a change in the illumination direction. A system which uses more than one biometric at the same time is known as a multi-modal verification system; it is often comprised of several modality experts and a decision stage. Since a multi-modal system uses complimentary discriminative information, lower error rates can be achieved; moreover, such a system can also be more robust, since the contribution of the modality affected by environmental conditions can be decreased. This thesis makes several contributions aimed at increasing the robustness of single- and multi-modal verification systems. Some of the major contributions are listed below. The robustness of a speech based system to ambient noise is increased by using Maximum Auto-Correlation Value (MACV) features, which utilize information from the source part of the speech signal. A new facial feature extraction technique is proposed (termed DCT-mod2), which utilizes polynomial coefficients derived from 2D Discrete Cosine Transform (DCT) coefficients of spatially neighbouring blocks. The DCT-mod2 features are shown to be robust to an illumination direction change as well as being over 80 times quicker to compute than 2D Gabor wavelet derived features. The fragility of Principal Component Analysis (PCA) derived features to an illumination direction change is solved by introducing a pre-processing step utilizing the DCT-mod2 feature extraction. We show that the enhanced PCA technique retains all the positive aspects of traditional PCA (that is, robustness to compression artefacts and white Gaussian noise) while also being robust to the illumination direction change. Several new methods, for use in fusion of speech and face information under noisy conditions, are proposed; these include a weight adjustment procedure, which explicitly measures the quality of the speech signal, and a decision stage comprised of a structurally noise resistant piece-wise linear classifier, which attempts to minimize the effects of noisy conditions via structural constraints on the decision boundary.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Microelectronic Engineering
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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.

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Our purpose with this thesis was to find biometric methods that can be used in access control of mobile access. The access control has two parts. Firstly, to validate the identity of the caller and, secondly, to ensure the validated user is not changed during the session that follows. Any solution to the access control problem is not available today, which means that anyone can get access to the mobile phone and the Internet. Therefore we have researched after a solution that can solve this problem but also on how to secure that no one else can take over an already validated session. We began to search for biometric methods that are available today to find them that would be best suited together with a mobile phone. After we had read information about them we did choose three methods for further investigation. These methods were Fingerprint Recognition, Iris Scan and Speaker Verification. Iris Scan is the method that is best suited to solve the authentication problem. The reasons for this are many. One of them is the uniqueness and stability of the iris, not even identical twins or the pair of the same individual has the same iris minutiae. The iris is also very protected behind eyelids, cornea and the aqueous humor and therefore difficult to damage. When it comes to the method itself, is it one of the most secure methods available today. One of the reasons for this is that the equal error rate is better than one in a million. However, this rate can be even better. It all depends on the Hamming Distance, which is a value that show how different the saved and temporarily template are, and what it is set to. To solve our session authentication, which was to make sure that no one else could take over a connected mobile phone, a sensor plate is the answer. This sensor will be able to sense for touch, heat and pulse. These three sensor measurements will together secure a validated session since the mobile phone will disconnect if the sensor looses its sensor data. There are, however, technological and other challenges to be solved before our proposed solutions will become viable. We address some of these issues in our thesis.
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Válková, 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.

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This thesis introduces readers to the basic types of the text and information inputs and processing to the computer. Thesis also includes historical contexts, current trends and future perspective of computer data input technologies and their use in practice. The first part of the thesis is a summary of a particular forms of entering and processing of the text data and information. The following part presents technological trends on the market concentrated on the automatic speech recognition systems along with the possibilities of their application in the business sphere. The rest of the thesis consists of a survey between Czech IT companies and based on it's results comes a suggestion of which technologies should be used as a part of the information systems.
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Atah, 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.

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Patino, Villar José María. "Efficient speaker diarization and low-latency speaker spotting". Thesis, Sorbonne université, 2019. http://www.theses.fr/2019SORUS003/document.

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La segmentation et le regroupement en locuteurs (SRL) impliquent la détection des locuteurs dans un flux audio et les intervalles pendant lesquels chaque locuteur est actif, c'est-à-dire la détermination de ‘qui parle quand’. La première partie des travaux présentés dans cette thèse exploite une approche de modélisation du locuteur utilisant des clés binaires (BKs) comme solution à la SRL. La modélisation BK est efficace et fonctionne sans données d'entraînement externes, car elle utilise uniquement des données de test. Les contributions présentées incluent l'extraction des BKs basée sur l'analyse spectrale multi-résolution, la détection explicite des changements de locuteurs utilisant les BKs, ainsi que les techniques de fusion SRL qui combinent les avantages des BKs et des solutions basées sur un apprentissage approfondi. La tâche de la SRL est étroitement liée à celle de la reconnaissance ou de la détection du locuteur, qui consiste à comparer deux segments de parole et à déterminer s'ils ont été prononcés par le même locuteur ou non. Même si de nombreuses applications pratiques nécessitent leur combinaison, les deux tâches sont traditionnellement exécutées indépendamment l'une de l'autre. La deuxième partie de cette thèse porte sur une application où les solutions de SRL et de reconnaissance des locuteurs sont réunies. La nouvelle tâche, appelée détection de locuteurs à faible latence, consiste à détecter rapidement les locuteurs connus dans des flux audio à locuteurs multiples. Il s'agit de repenser la SRL en ligne et la manière dont les sous-systèmes de SRL et de détection devraient être combinés au mieux
Speaker 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
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Książki na temat "Voice biometrics"

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García-Mateo, Carmen, i Gérard Chollet, red. Voice Biometrics: Technology, trust and security. Institution of Engineering and Technology, 2021. http://dx.doi.org/10.1049/pbse012e.

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Chollet, Gérard, i Carmen García-Mateo. Voice Biometrics: Technology, Trust and Security. Institution of Engineering & Technology, 2021.

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Chollet, Gérard, i Carmen García-Mateo. Voice Biometrics: Technology, Trust and Security. Institution of Engineering & Technology, 2020.

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Fairhurst, Michael. Biometrics: A Very Short Introduction. Oxford University Press, 2018. http://dx.doi.org/10.1093/actrade/9780198809104.001.0001.

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Biometrics is the scientific discipline of identifying individuals by means of the measurement of unique personal attributes, such as facial appearance, fingerprints, iris patterning, the voice, the way we write, and the way we walk. The new technologies of biometrics have a wide range of practical applications, from securing mobile phones and laptops to establishing identity in bank transactions, travel documents, and national identity cards. Biometrics: A Very Short Introduction considers the capabilities of biometrics-based identity checking and looks at the basic techniques in use today, developments in system design, and emerging technologies. It also explores the benefits and limitations of biometrics technologies, and how they can effectively support our increasingly interconnected society.
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Chesher, Chris. Invocational Media. Bloomsbury Publishing Plc, 2023. http://dx.doi.org/10.5040/9781501363597.

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Invocational Media critiques the sociotechnical power of digital technologies by introducing the concept of invocational media. What is an invocation? Ask your voice assistant and it will define it for you. It is a media artefact that responds to many invocations such as seeking the weather forecast, requesting any song you can name, or turning on the lights, almost magically. This contemporary manifestation of the ancient practice of invocation gives an immediate response to your call in a way that Chris Chesher argues is the characteristic power of all computers, which he redefines as invocational media. This book challenges the foundations of computer science by offering invocation as a powerful new way of conceptualising digital technologies. Drawing on media philosophy, Deleuze, Guattari, Heidegger, Latour, Austin, Innis and McLuhan, it critiques the representationalism of data processing, artificial intelligence and virtual reality. Invocational media seem to empower individuals, but necessarily subject users to corporate and government monopolies of invocation. They offer many ‘solutions’, but only by reducing everything to the same kind of act. They complicate agency in their indifference as to whether invokers are human or non-human. With robotics they invoke material form to act physically and autonomously. People willingly make themselves invocable to surveillance and control by creating their own profiles and marking themselves with biometrics. This ground-breaking book will change how you think about digital media by showing they are, in fact, invocational media.
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Części książek na temat "Voice biometrics"

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Toledano, Doroteo T., Joaquin Gonzalez-Rodriguez i Javier Ortega-Garcia. "Voice Device". W Encyclopedia of Biometrics, 1377–82. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-73003-5_15.

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Toledano, Doroteo T., Joaquín González-Rodríguez i Javier Ortega-Garcia. "Voice Device". W Encyclopedia of Biometrics, 1581–87. Boston, MA: Springer US, 2015. http://dx.doi.org/10.1007/978-1-4899-7488-4_15.

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Schroeter, Juergen, i Alistair Conkie. "Voice Sample Synthesis". W Encyclopedia of Biometrics, 1–8. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-27733-7_6-3.

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Wagner, Michael. "Anti-spoofing: Voice". W Encyclopedia of Biometrics, 1–11. Boston, MA: Springer US, 2014. http://dx.doi.org/10.1007/978-3-642-27733-7_70-3.

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Schroeter, Juergen. "Voice Sample Synthesis". W Encyclopedia of Biometrics, 1382–88. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-73003-5_6.

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Schroeter, Juergen, i Alistair Conkie. "Voice Sample Synthesis". W Encyclopedia of Biometrics, 1587–94. Boston, MA: Springer US, 2015. http://dx.doi.org/10.1007/978-1-4899-7488-4_6.

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Wagner, Michael. "Anti-spoofing, Voice". W Encyclopedia of Biometrics, 105–14. Boston, MA: Springer US, 2015. http://dx.doi.org/10.1007/978-1-4899-7488-4_70.

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Alegre, Federico, Nicholas Evans, Tomi Kinnunen, Zhizheng Wu i Junichi Yamagishi. "Anti-Spoofing: Voice Databases". W Encyclopedia of Biometrics, 1–7. Boston, MA: Springer US, 2014. http://dx.doi.org/10.1007/978-3-642-27733-7_9048-2.

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Evans, Nicholas, Federico Alegre, Zhizheng Wu i Tomi Kinnunen. "Anti-spoofing: Voice Conversion". W Encyclopedia of Biometrics, 1–10. Boston, MA: Springer US, 2014. http://dx.doi.org/10.1007/978-3-642-27733-7_9111-2.

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Drygajlo, Andrzej. "Voice, Forensic Evidence of". W Encyclopedia of Biometrics, 1–10. Boston, MA: Springer US, 2014. http://dx.doi.org/10.1007/978-3-642-27733-7_104-3.

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Streszczenia konferencji na temat "Voice biometrics"

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Pydala, Bhasha, M. Bhargavi, Balaji Vyshnavi, Machavaram Gopi Krishna, Aravadasari Lenin Kumar i K. Hima Bindu. "AI-Based Home Automation Using Voice Recognition and Biometric Finger Print Authentication". W 2024 International Conference on Expert Clouds and Applications (ICOECA), 727–31. IEEE, 2024. http://dx.doi.org/10.1109/icoeca62351.2024.00131.

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Uzan, Lior, i Lior Wolf. "I know that voice: Identifying the voice actor behind the voice". W 2015 International Conference on Biometrics (ICB). IEEE, 2015. http://dx.doi.org/10.1109/icb.2015.7139074.

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Zhang, Yushi, i Waleed H. Abdulla. "Voice as a Robust Biometrics". W 2008 Second International Conference on Future Generation Communication and Networking (FGCN). IEEE, 2008. http://dx.doi.org/10.1109/fgcn.2008.198.

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Chovancova, E., Z. Dudlakova, O. Fortotira i J. Radusovsky. "Multicore processor focused on voice biometrics". W 2014 IEEE 12th International Conference on Emerging eLearning Technologies and Applications (ICETA). IEEE, 2014. http://dx.doi.org/10.1109/iceta.2014.7107551.

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Gorodnichy, Dmitry O., Michael Thieme, David Bissessar, Jessica Chung, Elan Dubrofsky i Jonathon Lee. "C-BET evaluation of voice biometrics". W SPIE Defense, Security, and Sensing, redaktorzy Sárka O. Southern, Kevin N. Montgomery, Carl W. Taylor, Bernhard H. Weigl, B. V. K. Vijaya Kumar, Salil Prabhakar i Arun A. Ross. SPIE, 2011. http://dx.doi.org/10.1117/12.883533.

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Pani, Sushanta K., Anurag Chowdhury, Morgan Sandler i Arun Ross. "Voice Morphing: Two Identities in One Voice". W 2023 International Conference of the Biometrics Special Interest Group (BIOSIG). IEEE, 2023. http://dx.doi.org/10.1109/biosig58226.2023.10345989.

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Chetty, Girija, i Michael Wagner. "Multi-Level Liveness Verification for Face-Voice Biometric Authentication". W 2006 Biometrics Symposium: Special Session on Research at the Biometric Consortium Conference. IEEE, 2006. http://dx.doi.org/10.1109/bcc.2006.4341615.

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Tadeusiewicz, Ryszard, i Gražyna Demenko. "Voice as a Key". W 2009 International Conference on Biometrics and Kansei Engineering, ICBAKE. IEEE, 2009. http://dx.doi.org/10.1109/icbake.2009.28.

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Gomez-Alanis, Alejandro, Jose A. Gonzalez i Antonio M. Peinado. "Adversarial Transformation of Spoofing Attacks for Voice Biometrics". W IberSPEECH 2021. ISCA: ISCA, 2021. http://dx.doi.org/10.21437/iberspeech.2021-54.

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Bekkanti, Nikhitha, Leah Busch i Scott Amman. "Evaluation of Voice Biometrics for Identification and Authentication". W SAE WCX Digital Summit. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2021. http://dx.doi.org/10.4271/2021-01-0262.

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Raporty organizacyjne na temat "Voice biometrics"

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Kang, George S., i Yvette Lee. Voice Biometrics for Information Assurance Applications. Fort Belvoir, VA: Defense Technical Information Center, grudzień 2002. http://dx.doi.org/10.21236/ada408449.

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Harriss, Lydia, i Khalil Davis. Biometric Technologies. Parliamentary Office of Science and Technology, czerwiec 2018. http://dx.doi.org/10.58248/pn578.

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Biometric technologies identify individuals based on their distinguishing physical and behavioural attributes, such as fingerprints, face, and voice. Unlike passwords or traditional identity documents, biometric attributes are inherently linked to a person and cannot usually be lost or forgotten, potentially providing greater security and convenience. This briefing focuses on how these technologies work, their applications, and the policy challenges raised by their use.
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