995 resultados para Speaker Verification Technology


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Presently different audio watermarking methods are available; most of them inclined towards copyright protection and copy protection. This is the key motive for the notion to develop a speaker verification scheme that guar- antees non-repudiation services and the thesis is its outcome. The research presented in this thesis scrutinizes the field of audio water- marking and the outcome is a speaker verification scheme that is proficient in addressing issues allied to non-repudiation to a great extent. This work aimed in developing novel audio watermarking schemes utilizing the fun- damental ideas of Fast-Fourier Transform (FFT) or Fast Walsh-Hadamard Transform (FWHT). The Mel-Frequency Cepstral Coefficients (MFCC) the best parametric representation of the acoustic signals along with few other key acoustic characteristics is employed in crafting of new schemes. The au- dio watermark created is entirely dependent to the acoustic features, hence named as FeatureMark and is crucial in this work. In any watermarking scheme, the quality of the extracted watermark de- pends exclusively on the pre-processing action and in this work framing and windowing techniques are involved. The theme non-repudiation provides immense significance in the audio watermarking schemes proposed in this work. Modification of the signal spectrum is achieved in a variety of ways by selecting appropriate FFT/FWHT coefficients and the watermarking schemes were evaluated for imperceptibility, robustness and capacity char- acteristics. The proposed schemes are unequivocally effective in terms of maintaining the sound quality, retrieving the embedded FeatureMark and in terms of the capacity to hold the mark bits. Robust nature of these marking schemes is achieved with the help of syn- chronization codes such as Barker Code with FFT based FeatureMarking scheme and Walsh Code with FWHT based FeatureMarking scheme. An- other important feature associated with this scheme is the employment of an encryption scheme towards the preparation of its FeatureMark that scrambles the signal features that helps to keep the signal features unreve- laed. A comparative study with the existing watermarking schemes and the ex- periments to evaluate imperceptibility, robustness and capacity tests guar- antee that the proposed schemes can be baselined as efficient audio water- marking schemes. The four new digital audio watermarking algorithms in terms of their performance are remarkable thereby opening more opportu- nities for further research.

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This paper presents a study on wavelets and their characteristics for the specific purpose of serving as a feature extraction tool for speaker verification (SV), considering a Radial Basis Function (RBF) classifier, which is a particular type of Artificial Neural Network (ANN). Examining characteristics such as support-size, frequency and phase responses, amongst others, we show how Discrete Wavelet Transforms (DWTs), particularly the ones which derive from Finite Impulse Response (FIR) filters, can be used to extract important features from a speech signal which are useful for SV. Lastly, an SV algorithm based on the concepts presented is described.

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Tässä diplomityössä perehdytään puhujantunnistukseen ja sen käyttökelpoisuuteen käyttäjän henkilöllisyyden todentamisessa osana puhelinverkon lisäarvopalveluja. Puhelimitse ohjattavat palvelut ovat yleensä perustuneet puhelimen näppäimillä lähetettäviin äänitaajuusvalintoihin. Käyttäjän henkilöllisyydestä on voitu varmistua esimerkiksi käyttäjätunnuksen ja salaisen tunnusluvun perusteella. Tulevaisuudessa palvelut voivat perustua puheentunnistukseen, jolloin myös käyttäjän todentaminen äänen perusteella vaikuttaa järkevältä. Työssä esitellään aluksi erilaisia biometrisiä tunnistamismenetelmiä. Työssä perehdytään tarkemmin äänen perusteella tapahtuvaan puhujan todentamiseen. Työn käytännön osuudessa toteutettiin puhelinverkon palveluihin soveltuva puhujantodennussovelluksen prototyyppi. Työn tarkoituksena oli selvittää teknologian käyttömahdollisuuksia sekä kerätä kokemusta puhujantodennuspalvelun toteuttamisesta tulevaisuutta silmällä pitäen. Prototyypin toteutuksessa ohjelmointikielenä käytettiin Javaa.

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Speaker Recognition, Speaker Verification, Sparse Kernel Logistic Regression, Support Vector Machine

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Phonation distortion leaves relevant marks in a speaker's biometric profile. Dysphonic voice production may be used for biometrical speaker characterization. In the present paper phonation features derived from the glottal source (GS) parameterization, after vocal tract inversion, is proposed for dysphonic voice characterization in Speaker Verification tasks. The glottal source derived parameters are matched in a forensic evaluation framework defining a distance-based metric specification. The phonation segments used in the study are derived from fillers, long vowels, and other phonation segments produced in spontaneous telephone conversations. Phonated segments from a telephonic database of 100 male Spanish native speakers are combined in a 10-fold cross-validation task to produce the set of quality measurements outlined in the paper. Shimmer, mucosal wave correlate, vocal fold cover biomechanical parameter unbalance and a subset of the GS cepstral profile produce accuracy rates as high as 99.57 for a wide threshold interval (62.08-75.04%). An Equal Error Rate of 0.64 % can be granted. The proposed metric framework is shown to behave more fairly than classical likelihood ratios in supporting the hypothesis of the defense vs that of the prosecution, thus ofering a more reliable evaluation scoring. Possible applications are Speaker Verification and Dysphonic Voice Grading.

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This paper predicts speech synthesis, speech recognition, and speaker recognition technology for the year 2001, and it describes the most important research problems to be solved in order to arrive at these ultimate synthesis and recognition systems. The problems for speech synthesis include natural and intelligible voice production, prosody control based on meaning, capability of controlling synthesized voice quality and choosing individual speaking style, multilingual and multidialectal synthesis, choice of application-oriented speaking styles, capability of adding emotion, and synthesis from concepts. The problems for speech recognition include robust recognition against speech variations, adaptation/normalization to variations due to environmental conditions and speakers, automatic knowledge acquisition for acoustic and linguistic modeling, spontaneous speech recognition, naturalness and ease of human-machine interaction, and recognition of emotion. The problems for speaker recognition are similar to those for speech recognition. The research topics related to all these techniques include the use of articulatory and perceptual constraints and evaluation methods for measuring the quality of technology and systems.

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Speech interface technology, which includes automatic speech recognition, synthetic speech, and natural language processing, is beginning to have a significant impact on business and personal computer use. Today, powerful and inexpensive microprocessors and improved algorithms are driving commercial applications in computer command, consumer, data entry, speech-to-text, telephone, and voice verification. Robust speaker-independent recognition systems for command and navigation in personal computers are now available; telephone-based transaction and database inquiry systems using both speech synthesis and recognition are coming into use. Large-vocabulary speech interface systems for document creation and read-aloud proofing are expanding beyond niche markets. Today's applications represent a small preview of a rich future for speech interface technology that will eventually replace keyboards with microphones and loud-speakers to give easy accessibility to increasingly intelligent machines.

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EPA symbol on cover.

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A large percentage of pile caps support only one column, and the pile caps in turn are supported by only a few piles. These are typically short and deep members with overall span-depth ratios of less than 1.5. Codes of practice do not provide uniform treatment for the design of these types of pile caps. These members have traditionally been designed as beams spanning between piles with the depth selected to avoid shear failures and the amount of longitudinal reinforcement selected to provide sufficient flexural capacity as calculated by the engineering beam theory. More recently, the strut-and-tie method has been used for the design of pile caps (disturbed or D-region) in which the load path is envisaged to be a three-dimensional truss, with compressive forces being supported by concrete compressive struts between the column and piles and tensile forces being carried by reinforcing steel located between piles. Both of these models have not provided uniform factors of safety against failure or been able to predict whether failure will occur by flexure (ductile mode) or shear (fragile mode). In this paper, an analytical model based on the strut-and-tie approach is presented. The proposed model has been calibrated using an extensive experimental database of pile caps subjected to compression and evaluated analytically for more complex loading conditions. It has been proven to be applicable across a broad range of test data and can predict the failures modes, cracking, yielding, and failure loads of four-pile caps with reasonable accuracy.

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Dissertação para obtenção do Grau de Doutor em Engenharia Biomédica

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This study is part of an ongoing collaborative effort between the medical and the signal processing communities to promote research on applying standard Automatic Speech Recognition (ASR) techniques for the automatic diagnosis of patients with severe obstructive sleep apnoea (OSA). Early detection of severe apnoea cases is important so that patients can receive early treatment. Effective ASR-based detection could dramatically cut medical testing time. Working with a carefully designed speech database of healthy and apnoea subjects, we describe an acoustic search for distinctive apnoea voice characteristics. We also study abnormal nasalization in OSA patients by modelling vowels in nasal and nonnasal phonetic contexts using Gaussian Mixture Model (GMM) pattern recognition on speech spectra. Finally, we present experimental findings regarding the discriminative power of GMMs applied to severe apnoea detection. We have achieved an 81% correct classification rate, which is very promising and underpins the interest in this line of inquiry.

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Biometric system performance can be improved by means of data fusion. Several kinds of information can be fused in order to obtain a more accurate classification (identification or verification) of an input sample. In this paper we present a method for computing the weights in a weighted sum fusion for score combinations, by means of a likelihood model. The maximum likelihood estimation is set as a linear programming problem. The scores are derived from a GMM classifier working on a different feature extractor. Our experimental results assesed the robustness of the system in front a changes on time (different sessions) and robustness in front a change of microphone. The improvements obtained were significantly better (error bars of two standard deviations) than a uniform weighted sum or a uniform weighted product or the best single classifier. The proposed method scales computationaly with the number of scores to be fussioned as the simplex method for linear programming.

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The current means and methods of verifying that high-strength bolts have been properly tightened are very laborious and time consuming. In some cases, the techniques require special equipment and, in other cases, the verification itself may be somewhat subjective. While some commercially available verification techniques do exist, these options still have some limitations and might be considered costly options. The main objectives of this project were to explore high-strength bolt-tightening and verification techniques and to investigate the feasibility of developing and implementing new alternatives. A literature search and a survey of state departments of transportation (DOTs) were conducted to collect information on various bolt-tightening techniques such that an understanding of available and under-development techniques could be obtained. During the literature review, the requirements for materials, inspection, and installation methods outlined in the Research Council on Structural Connections specification were also reviewed and summarized. To guide the search for finding new alternatives and technology development, a working group meeting was held at the Iowa State University Institute for Transportation October 12, 2015. During the meeting, topics central to the research were discussed with Iowa DOT engineers and other professionals who have relevant experiences.

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Commercially available haptic interfaces are usable for many purposes. However, as generic devices they are not the most suitable for the control of heavy duty mobile working machines like mining machines, container handling equipment and excavators. Alternative mechanical constructions for a haptic controller are presented and analysed. A virtual reality environment (VRE) was built to test the proposed haptic controller mechanisms. Verification of an electric motor emulating a hydraulic pump in the electro-hydraulic system of a mobile working machine is carried out. A real-time simulator using multi-body-dynamics based software with hardware-in-loop (HIL) setup was used for the tests. Recommendations for further development of a haptic controller and emulator electric motor are given.

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The capabilities and thus, design complexity of VLSI-based embedded systems have increased tremendously in recent years, riding the wave of Moore’s law. The time-to-market requirements are also shrinking, imposing challenges to the designers, which in turn, seek to adopt new design methods to increase their productivity. As an answer to these new pressures, modern day systems have moved towards on-chip multiprocessing technologies. New architectures have emerged in on-chip multiprocessing in order to utilize the tremendous advances of fabrication technology. Platform-based design is a possible solution in addressing these challenges. The principle behind the approach is to separate the functionality of an application from the organization and communication architecture of hardware platform at several levels of abstraction. The existing design methodologies pertaining to platform-based design approach don’t provide full automation at every level of the design processes, and sometimes, the co-design of platform-based systems lead to sub-optimal systems. In addition, the design productivity gap in multiprocessor systems remain a key challenge due to existing design methodologies. This thesis addresses the aforementioned challenges and discusses the creation of a development framework for a platform-based system design, in the context of the SegBus platform - a distributed communication architecture. This research aims to provide automated procedures for platform design and application mapping. Structural verification support is also featured thus ensuring correct-by-design platforms. The solution is based on a model-based process. Both the platform and the application are modeled using the Unified Modeling Language. This thesis develops a Domain Specific Language to support platform modeling based on a corresponding UML profile. Object Constraint Language constraints are used to support structurally correct platform construction. An emulator is thus introduced to allow as much as possible accurate performance estimation of the solution, at high abstraction levels. VHDL code is automatically generated, in the form of “snippets” to be employed in the arbiter modules of the platform, as required by the application. The resulting framework is applied in building an actual design solution for an MP3 stereo audio decoder application.