Relevant bibliographies by topics / Speech biometrics

Academic literature on the topic 'Speech biometrics'

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Published: 4 June 2021
Last updated: 20 February 2023

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Journal articles on the topic "Speech biometrics"

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Sayoud, Halim. "Biometrics." International Journal of Technoethics 2, no. 1 (January 2011): 19–34. http://dx.doi.org/10.4018/jte.2011010102.

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The term biometrics is derived from the Greek words: bio (life) and metrics (to measure). “Biometric technologies” are defined as automated methods of verifying or recognizing the identity of a living person based on a physiological or behavioral characteristic. Several techniques and features were used over time to recognize human beings several years before the birth of Christ. Today, this research field has become very employed in many applications such as security applications, multimedia applications and banking applications. Also, many methods have been developed to strengthen the biometric accuracy and reduce the imposture errors by using several features such as face, speech, iris, finger vein, etc. From a security purpose and economic point of view, biometrics has brought a great benefit and has become an important tool for governments and institutions. However, citizens are expressing their thorough worry, which is due to the freedom limitations and loss of privacy. This paper briefly presents some new technologies that have recently been proposed in biometrics with their levels of reliability, and discusses the different social and ethic problems that may result from the abusive use of these technologies.
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Gupta, Vikas, Shashikant Garade, Shriyash Kothekar, Darshana Meshram, Shraddha Wankhede, and Prof Rajshri Pote. "An Investigative Study of Voice Functioned Smart Door Lock System." International Journal of Research Publication and Reviews 04, no. 01 (2023): 1920–24. http://dx.doi.org/10.55248/gengpi.2023.4154.

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This article discusses how speech recognition can improve security for persons and property while making door systems more accessible to people with impairments. Facial recognition, fingerprint scanning, and iris scanning are examples of popular biometric technologies. Based on features and qualities used to identify various people for the safety and security of their lives and property, these biometric identifiers are distinctive and one-of a-kind. Sadly, these biometrics are vulnerable to hacking. A pin or password can be cracked, a person's finger can be severed to perform a fingerprint scan, an eyeball can be removed to perform an iris scan, and a person's photo can be used to perform facial recognition. With the help of speech recognition biometrics technology, these obstacles can be reduced. Technology for voice biometrics is more precise, swifter, more practical. In order to give individuals a quick way to open their doors and simultaneously protect their safety and security, this research study intends to design a door access control system that makes use of voice recognition algorithms. The testing phase and the training phase are the two phases that make up the system. The attributes of a speech are extracted and stored in a database during the training phase. Using voice recognition algorithms and vocal models, the intents from a person's address would be derived during the testing phase. A user is given access if a match is detected.
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Kinge, Steve. "Freedom of speech: Using speech biometrics for user verification." Network Security 2007, no. 1 (January 2007): 12–14. http://dx.doi.org/10.1016/s1353-4858(07)70006-5.

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Dinesh, Archana, and K. Edet Bijoy. "Computations on Cipher Speech for Secure Biometrics." Procedia Computer Science 93 (2016): 774–81. http://dx.doi.org/10.1016/j.procs.2016.07.293.

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Teoh, Andrew Beng Jin, and Lu Leng. "Special Issue on Advanced Biometrics with Deep Learning." Applied Sciences 10, no. 13 (June 28, 2020): 4453. http://dx.doi.org/10.3390/app10134453.

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Moreno, L. C., and P. B. Lopes. "The Voice Biometrics Based on Pitch Replication." International Journal for Innovation Education and Research 6, no. 10 (October 31, 2018): 351–58. http://dx.doi.org/10.31686/ijier.vol6.iss10.1201.

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Authentication and security in automated systems have become very much necessary in our days and many techniques have been proposed towards this end. One of these alternatives is biometrics in which human body characteristics are used to authenticate the system user. The objective of this article is to present a method of text independent speaker identification through the replication of pitch characteristics. Pitch is an important speech feature and is used in a variety of applications, including voice biometrics. The proposed method of speaker identification is based on short segments of speech, namely, three seconds for training and three seconds for the speaker determination. From these segments pitch characteristics are extracted and are used in the proposed method of replication for identification of the speaker.
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Setiawan, Ariyono. "Pengenalan Bentuk dan Pola Suara bagi Anak Anak Penyandang Tuna Rungu." Jurnal Penelitian 3, no. 2 (June 4, 2018): 57–65. http://dx.doi.org/10.46491/jp.v3e2.38.57-65.

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IInability to speak for the Deaf child is a distinctive characteristic that makes it different from normal children. Children with normal hearing understand the language through hearing in the months before they start talking. Speech recognition or recognition of voice patterns in children Deaf as search forms grades suitability and appropriateness. the type of sound is a development from techniques and systems that enable the computer to accept input in the form of patterns spoken word so on get the value of the type of words approaches, and can be understood. This study proposes a solution in Method utilizes biometrics to recognize the type of sound patterns deaf children who will be in the skewer with the sound of a normal child. Biometric methods used in digital signal processing (in this case sound) in the form of discrete biometrics refers to the automatic identification of humans by psikological or basic human characteristic sound.
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Rukhiran, Meennapa, Sorapak Pukdesree, and Paniti Netinant. "Biometric Cloud Services for Web-Based Examinations." International Journal of Information Technology and Web Engineering 17, no. 1 (January 2022): 1–25. http://dx.doi.org/10.4018/ijitwe.299022.

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Biometric recognition may be used in conjunction with human authentication on a smartphone to improve accuracy, reliability, and simplicity, and to aid in fraud prevention and user authentication. While single biometric authentication addresses environmental degradation and sensor noise limitations, and the single point of failure scenario in biometric systems can result in more robust biometric systems, multimodal biometric authentication can improve the accuracy of identification and recognition. The purpose of this research is to propose a facial and speech authentication system that is cloud-based and supports a web-based examination approach. The system enables students' biometrics to be registered, students to be recognized, and student recognition results to be reported. The confusion matrix is used to compare the results of positive and negative detection in various ways, including accuracy score, precision value, and recall value. Adaptive multimodal biometric authentication should be designed and evaluated for further research using the optimal weights for each biometric.
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Cherif, Youssouf Ismail, and Abdelhakim Dahimene. "IMPROVED VOICE-BASED BIOMETRICS USING MULTI-CHANNEL TRANSFER LEARNING." IADIS INTERNATIONAL JOURNAL ON COMPUTER SCIENCE AND INFORMATION SYSTEMS 15, no. 1 (October 7, 2020): 99–113. http://dx.doi.org/10.33965/ijcsis_2020150108.

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Identifying the speaker has become more of an imperative thing to do in the modern age. Especially since most personal and professional appliances rely on voice commands or speech in general terms to operate. These systems need to discern the identity of the speaker rather than just the words that have been said to be both smart and safe. Especially if we consider the numerous advanced methods that have been developed to generate fake speech segments. The objective of this paper is to improve upon the existing voice-based biometrics to keep up with these synthesizers. The proposed method focuses on defining a novel and more speaker adapted features by implying artificial neural networks and transfer learning. The approach uses pre-trained networks to define a mapping from two complementary acoustic features to a speaker adapted phonetic features. The complementary acoustics features are paired to provide both information about how the speech segments are perceived (type 1 feature) and produced (type 2 feature). The approach was evaluated using both a small and large closed-speaker data set. Primary results are encouraging and confirm the usefulness of such an approach to extract speaker adapted features whether for classical machine learning algorithms or advanced neural structures such as LSTM or CNN.
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Besacier, L., P. Mayorga, J. F. Bonastre, C. Fredouille, and S. Meignier. "Overview of compression and packet loss effects in speech biometrics." IEE Proceedings - Vision, Image, and Signal Processing 150, no. 6 (2003): 372. http://dx.doi.org/10.1049/ip-vis:20031033.

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Dissertations / Theses on the topic "Speech biometrics"

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Sanderson, Conrad, and 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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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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Kotulek, Milan. "Jednoduchý textově nezávislý hlasový zámek - Softwarový systém pro verifikaci mluvčích." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2015. http://www.nusl.cz/ntk/nusl-221256.

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A brief introduction into biometrics is described in this thesis leading to description and to design a solution of verification system using speech analysis. The designed system provides firstly basic signal processing, then vowel recognition in fluent Czech speech. For each found vowel, observed speech features are calculated. The created GUI application was tested on created speaker database and its efficiency is approximately 54 % for short testing utterances, and approx. 88 % for long testing utterances respectively.
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Melin, Håkan. "Automatic speaker verification on site and by telephone: methods, applications and assessment." Doctoral thesis, KTH, Tal, musik och hörsel, TMH, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-4242.

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Speaker verification is the biometric task of authenticating a claimed identity by means of analyzing a spoken sample of the claimant's voice. The present thesis deals with various topics related to automatic speaker verification (ASV) in the context of its commercial applications, characterized by co-operative users, user-friendly interfaces, and requirements for small amounts of enrollment and test data. A text-dependent system based on hidden Markov models (HMM) was developed and used to conduct experiments, including a comparison between visual and aural strategies for prompting claimants for randomized digit strings. It was found that aural prompts lead to more errors in spoken responses and that visually prompted utterances performed marginally better in ASV, given that enrollment data were visually prompted. High-resolution flooring techniques were proposed for variance estimation in the HMMs, but results showed no improvement over the standard method of using target-independent variances copied from a background model. These experiments were performed on Gandalf, a Swedish speaker verification telephone corpus with 86 client speakers. A complete on-site application (PER), a physical access control system securing a gate in a reverberant stairway, was implemented based on a combination of the HMM and a Gaussian mixture model based system. Users were authenticated by saying their proper name and a visually prompted, random sequence of digits after having enrolled by speaking ten utterances of the same type. An evaluation was conducted with 54 out of 56 clients who succeeded to enroll. Semi-dedicated impostor attempts were also collected. An equal error rate (EER) of 2.4% was found for this system based on a single attempt per session and after retraining the system on PER-specific development data. On parallel telephone data collected using a telephone version of PER, 3.5% EER was found with landline and around 5% with mobile telephones. Impostor attempts in this case were same-handset attempts. Results also indicate that the distribution of false reject and false accept rates over target speakers are well described by beta distributions. A state-of-the-art commercial system was also tested on PER data with similar performance as the baseline research system.
QC 20100910
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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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Boško, Božilović. "Биометријско обележје за препознавање говорника: дводимензионална информациона ентропија говорног сигнала." Phd thesis, Univerzitet u Novom Sadu, Fakultet tehničkih nauka u Novom Sadu, 2016. http://www.cris.uns.ac.rs/record.jsf?recordId=101369&source=NDLTD&language=en.

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Mотив за истраживање је унапређење процеса аутоматског препознавања говорника без обзира на садржај изговоренoг текста.Циљ ове докторске дисертације је дефинисање новог биометријског обележја за препознавање говорника независно од изговореног текста − дводимензионалне информационе ентропије говорног сигнала.Дефинисање новог обележја се врши искључиво у временском домену, па је рачунарска сложеност алгоритма за његово издвајање знатно мања у односу на обележја која се издвајају у фреквенцијском домену. Оцена перформанси дводимензионалне информационе ентропије је урађена над репрезентативним скупом случајно одабраних говорника. Показано је да предложено обележје има малу варијабилност унутар говорног сигнала једног говорника, а велику варијабилност између говорних сигнала различитих говорника.
Motiv za istraživanje je unapređenje procesa automatskog prepoznavanja govornika bez obzira na sadržaj izgovorenog teksta.Cilj ove doktorske disertacije je definisanje novog biometrijskog obeležja za prepoznavanje govornika nezavisno od izgovorenog teksta − dvodimenzionalne informacione entropije govornog signala.Definisanje novog obeležja se vrši isključivo u vremenskom domenu, pa je računarska složenost algoritma za njegovo izdvajanje znatno manja u odnosu na obeležja koja se izdvajaju u frekvencijskom domenu. Ocena performansi dvodimenzionalne informacione entropije je urađena nad reprezentativnim skupom slučajno odabranih govornika. Pokazano je da predloženo obeležje ima malu varijabilnost unutar govornog signala jednog govornika, a veliku varijabilnost između govornih signala različitih govornika.
Тhe motivation for the research is the improvement of the automatic speaker recognition process regardless of the content of spoken text.The objective of this dissertation is to define a new biometric text-independent speaker recognition feature − the two-dimensional informational entropy of speech signal.Definition of the new feature is performed in time domain exclusively, so the computing complexity of the algorithm for feature extraction is significantly lower in comparison to feature extraction in spectral domain. Performance analysis of two-dimensional information entropy is performed on the representative set of randomly chosen speakers. It has been shown that new feature has small within-speaker variability and significant between-speaker variability.
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Chan, Siu Man. "Improved speaker verification with discrimination power weighting /." View abstract or full-text, 2004. http://library.ust.hk/cgi/db/thesis.pl?ELEC%202004%20CHANS.

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Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2004.
Includes bibliographical references (leaves 86-93). Also available in electronic version. Access restricted to campus users.
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Vlasenko, Andrej. "Studentų emocinės būklės testavimo metu tyrimas panauduojant biometrines technologijas." Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2012. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2012~D_20120329_153219-37955.

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Disertacijoje nagrinėjamas kompiuterinės sistemos kūrimas, su kuria būtų galima nustatyti asmens psichoemicinę būseną pagal jo balso signalų požymius. Taip pat pateikiama vyzdžio skersmens matavimo sistema. Taigi, pagrindiniai mokslinio tyrimo objektai yra žmogaus balso požymiai ir jo vyzdžio dydžio pa-sikeitimo dinamika. Pagrindinis disertacijos tikslas – sukurti metodikas ir algo-ritmus, skirtus automatiškai apdoroti ir išanalizuoti balso signalo požymius. Šių sukurtų algoritmų taikymo sritis – streso valdymo sistemos programinė įranga. Šiame darbe sprendžiami keli pagrindiniai uždaviniai: analizuojant kalbėtojo balsą, kalbančiojo psichoemocinės būklės identifikavimo galimybės ir vyzdžio dydžio kaitos dinamika. Disertaciją sudaro įvadas, keturi skyriai, rezultatų apibendrinimas, naudotos literatūros sąrašas ir autoriaus publikacijų disertacijos tema sąrašas. Įvade aptariama tiriamoji problema, darbo aktualumas, aprašomas tyrimų objektas, formuluojamas darbo tikslas bei uždaviniai, aprašoma tyrimų metodi-ka, darbo mokslinis naujumas, darbo rezultatų praktinė reikšmė, ginamieji teigi-niai. Įvado pabaigoje pristatomos disertacijos tema autoriaus paskelbtos publika-cijos bei pranešimai konferencijose ir disertacijos struktūra. Pirmajame skyriuje pateikta asmens biometrinių bei fiziologiniu požymiu analizės pagrindu sukurta „Rekomendacine biometrinė streso valdymo sistema” (angl. Recommended Biometric Stress Management System). Sistema gali padėti nustatyti neigiamą streso lygį... [toliau žr. visą tekstą]
The dissertation investigates the issues of creating a computer system that uses voice signal features to determine person’s emotional state. In addition pre-sented system of measuring pupil diameter.The main objects of research include emotion recognition from speech and dynamics of eye pupil size change.The main purpose of this dissertation is employing suitable methodologies and algo-rithms to automatically process and analyse human voice parameters. Created algorithms can be used in Stress Management System software. The dissertation also focuses on researching the possibilities of identification of speaker’s psy-choemotional state: applying the analysis of speaker’s voice parameters and the analysis of dynamics of eye pupil size change. The dissertation consists of four parts including Introduction, 4 chapters, Conclusions and References. The introduction reveals the investigated problem, importance of the thesis and the object of research and describes the purpose and tasks of the paper, re-search methodology, scientific novelty, the practical significance of results ex-amined in the paper and defended statements. The introduction ends in present-ing the author’s publications on the subject of the defended dissertation, offering the material of made presentations in conferences and defining the structure of the dissertation. Chapter 1- the Recommended Biometric Stress Management System found-ed on the speech analysis. The System can assist in determining the level of... [to full text]
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Hartung, Karin. "Biometrical approaches for analysing gene bank evaluation data on barley (Hordeum spec.)." [S.l. : s.n.], 2007. http://nbn-resolving.de/urn:nbn:de:bsz:100-opus-2251.

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Books on the topic "Speech biometrics"

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Zhang, David. 3D Biometrics: Systems and Applications. New York, NY: Springer New York, 2013.

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service), SpringerLink (Online, ed. Pattern Recognition, Machine Intelligence and Biometrics. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011.

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Travieso-González, Carlos M. Advances in Nonlinear Speech Processing: 5th International Conference on Nonlinear Speech Processing, NOLISP 2011, Las Palmas de Gran Canaria, Spain, November 7-9, 2011. Proceedings. Berlin, Heidelberg: Springer-Verlag GmbH Berlin Heidelberg, 2011.

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NATO Advanced Study Institute on the Fundamentals of Verbal and Nonverbal Communication and the Biometric Issue (2006 Vietri sul Mare, Italy). Fundamentals of verbal and nonverbal communication and the biometric issue. Washington, DC: IOS Press, 2007.

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1946-, Kittler Josef, and Nixon Mark S, eds. Audio-and video-based biometric person authentication: 4th International Conference, AVBPA 2003, Guildford, UK, June 2003 : proceedings. Berlin: Springer, 2003.

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AVBPA '97 ((1st 1997 Montana,Switzerland). Audio- and video-based biometric person authentication: First International Conference, AVBPA '97, Crans-Montana, Switzerland, March 1997 : proceedings. Berlin: Springer, 1997.

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International Conference, AVBPA (1st 1997 Montana, Switzerland). Audio- and video-based biometric person authentication: First International Conference, AVBPA '97, Crans-Montana, Switzerland, March 12-14, 1997 : proceedings. Berlin: Springer, 1997.

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Rainer, Stiefelhagen, and Garofolo John S, eds. Multimodal technologies for perception of humans: First International Evaluation Workshop on Classification of Events, Activities and Relationships, CLEAR 2006, Southampton, UK, April 6-7, 2006 : revised selected papers. Berlin: Springer, 2007.

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Rachel, Bowers, Fiscus Jonathan G, and SpringerLink (Online service), eds. Multimodal Technologies for Perception of Humans: International Evaluation Workshops CLEAR 2007 and RT 2007, Baltimore, MD, USA, May 8-11, 2007, Revised Selected Papers. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2008.

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Zhang, David, and Guangming Lu. 3D Biometrics: Systems and Applications. Springer, 2015.

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Book chapters on the topic "Speech biometrics"

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Docio-Fernandez, Laura, and Carmen Garcia-Mateo. "Speech Production." In Encyclopedia of Biometrics, 1290–95. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-73003-5_199.

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Toledano, Doroteo T., Daniel Ramos, Javier Gonzalez-Dominguez, and Joaquín González-Rodríguez. "Speech Analysis." In Encyclopedia of Biometrics, 1284–89. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-73003-5_200.

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Docio-Fernandez, Laura, and Carmen García Mateo. "Speech Production." In Encyclopedia of Biometrics, 1493–98. Boston, MA: Springer US, 2015. http://dx.doi.org/10.1007/978-1-4899-7488-4_199.

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Toledano, Doroteo T., Daniel Ramos, Javier Gonzalez-Dominguez, and Joaquín González-Rodríguez. "Speech Analysis." In Encyclopedia of Biometrics, 1487–93. Boston, MA: Springer US, 2015. http://dx.doi.org/10.1007/978-1-4899-7488-4_200.

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Harriero, Alberto, Daniel Ramos, Joaquin Gonzalez-Rodriguez, and Julian Fierrez. "Analysis of the Utility of Classical and Novel Speech Quality Measures for Speaker Verification." In Advances in Biometrics, 434–42. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01793-3_45.

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Dovydaitis, Laurynas, Tomas Rasymas, and Vytautas Rudžionis. "Speaker Authentication System Based on Voice Biometrics and Speech Recognition." In Business Information Systems Workshops, 79–84. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52464-1_8.

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Naseem, Imran, and Ajmal Mian. "User Verification by Combining Speech and Face Biometrics in Video." In Advances in Visual Computing, 482–92. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-89646-3_47.

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Moctezuma, Luis Alfredo, and Marta Molinas. "EEG-Based Subjects Identification Based on Biometrics of Imagined Speech Using EMD." In Brain Informatics, 458–67. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-05587-5_43.

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Chen, Ke. "Speaker Modeling with Various Speech Representations." In Biometric Authentication, 592–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25948-0_81.

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Ouzounov, Atanas. "Noisy Speech Endpoint Detection using Robust Feature." In Biometric Authentication, 105–17. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-13386-7_9.

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Conference papers on the topic "Speech biometrics"

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Sidnyaev, N. I., Iu I. Butenko, and A. D. Kiseleva. "Predicative analytics and speech biometrics." In INTERNATIONAL CONFERENCE ON INFORMATICS, TECHNOLOGY, AND ENGINEERING 2021 (InCITE 2021): Leveraging Smart Engineering. AIP Publishing, 2022. http://dx.doi.org/10.1063/5.0074672.

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Maes, Stéphane H. "Conversational biometrics." In 6th European Conference on Speech Communication and Technology (Eurospeech 1999). ISCA: ISCA, 1999. http://dx.doi.org/10.21437/eurospeech.1999-285.

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Agrafioti, Foteini, and Dimitrios Hatzinakos. "Signal validation for cardiac biometrics." In 2010 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2010. http://dx.doi.org/10.1109/icassp.2010.5495461.

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Mason and Brand. "The role of dynamics in visual speech biometrics." In IEEE International Conference on Acoustics Speech and Signal Processing ICASSP-02. IEEE, 2002. http://dx.doi.org/10.1109/icassp.2002.1004814.

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Mason, J. S., and J. D. Brand. "The role of dynamics in visual speech biometrics." In Proceedings of ICASSP '02. IEEE, 2002. http://dx.doi.org/10.1109/icassp.2002.5745553.

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Al-hamdani, Osama, Ali Chekima, Jamal Dargham, Sh-Hussain Salleh, Alias Mohd Noor, and Fuad Noman. "Multi-Biometrics Fusion (Heart Sound-Speech Authentication System)." In Imaging and Signal Processing in Health Care and Technology. Calgary,AB,Canada: ACTAPRESS, 2012. http://dx.doi.org/10.2316/p.2012.771-007.

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Vielhauer, Claus, T. K. Basu, Jana Dittmann, and Pranab K. Dutta. "Finding meta data in speech and handwriting biometrics." In Electronic Imaging 2005, edited by Edward J. Delp III and Ping W. Wong. SPIE, 2005. http://dx.doi.org/10.1117/12.585816.

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Huy Tran, Dat, Yi Ren Leng, and Haizhou Li. "Feature integration for heart sound biometrics." In 2010 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2010. http://dx.doi.org/10.1109/icassp.2010.5495476.

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Inthavisas, K., and D. Lopresti. "Speech cryptographic key regeneration based on password." In 2011 IEEE International Joint Conference on Biometrics (IJCB). IEEE, 2011. http://dx.doi.org/10.1109/ijcb.2011.6117553.

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Saeed, Khalid, and Adam Szczepanski. "A Study on Noisy Speech Recognition." In 2009 International Conference on Biometrics and Kansei Engineering, ICBAKE. IEEE, 2009. http://dx.doi.org/10.1109/icbake.2009.17.

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