Sharif Digital Repository

In this article a new scheme is proposed to use mean supervector in text-prompted speaker verification system. In this scheme, for each month name a subsystem is constructed and a final score based on passphrase is computed by the combination of the scores of these subsystems. Results from the telephony dataset of Persian month names show that the proposed method significantly reduces EER in comparison with the-State-of-the-art State-GMM-MAP method. Furthermore, it is shown that based on training set and testing set we can use 12 models per speaker instead of 220. Therefore, this scheme reduces EER and computational burden. In addition, the use of HMM instead of GMM as words' model improves... 

The duration of utterances is one of the effective factors on the performance of speaker verification systems. Text dependent speaker verification suffers from both short duration and unmatched content between enrollment and test segments. In this paper, we use Discriminative Gaussian Process Latent Variable Model (DGPLVM) to deal with the uncertainty caused by short duration. This is the first attempt to utilize Gaussian Process for speaker verification. Also, to manage the unmatched content between enrollment and test segments we proposed the localized-DGPLVM that trains DGPLVM for each phrase in dataset. Experiments show the relative improvement of 27.4% in EER on RSR2015  

In large population Speaker Identification (SI), computation time has become one of the most important issues in recent real time systems. Test computation time depends on the cost of likelihood computation between test features and registered speaker models. For real time application of speaker identification, system must identify an unknown speaker quickly. Hence the conventional SI methods cannot be used. In this paper, we propose a two-step method that utilizes two different identification methods. In the first step we use Nearest Neighbor method to decrease the search space. In the second step we use GMM-based SI methods to specify the target speaker. We achieved 3.5× speed-ups without... 

I-vectors have proved to be the most effective features for text-independent speaker verification in recent researches. In this article a new scheme is proposed to utilize i-vectors in text-prompted speaker verification in a simple while effective manner. In order to examine this scheme empirically, a telephony dataset of Persian month names is introduced. Experiments show that the proposed scheme reduces the EER by 31% compared to the state-of-the-art State-GMM-MAP method. Furthermore it is shown that using HMM instead of GMM for universal background modeling leads to 15% reduction in EER  

In this paper, we combine Hidden Markov Models HMMs with i-vector extractors to address the problem of text-dependent speaker recognition with random digit strings. We employ digit-specific HMMs to segment the utterances into digits, to perform frame alignment to HMM states and to extract Baum-Welch statistics. By making use of the natural partition of input features into digits, we train digit-specific i-vector extractors on top of each HMM and we extract well-localized i-vectors, each modelling merely the phonetic content corresponding to a single digit. We then examine ways to perform channel and uncertainty compensation, and we propose a novel method for using the uncertainty in the... 

By increasing the number of registered speakers in Speaker Identification (SI) systems, computation time for identifying an unknown speaker is significantly increased. This problem arises from the simple design of conventional methods. Due to this limitation, we cannot use conventional SI methods in real time applications. In this paper, we propose a two-step method to overcome this limitation. We use different identification methods for each step. In the first step we reduce the search space using Nearest Neighbor method. In the second step we identify the target speaker using the conventional GMM-based SI method. The experimental results show 3.4× speed-ups without any accuracy loss using... 

The low-dimensional i-vector representation of speech segments is used in the state-of-the-art text-independent speaker verification systems. However, i-vectors were deemed unsuitable for the text-dependent task, where simpler and older speaker recognition approaches were found more effective. In this work, we propose a straightforward hidden Markov model (HMM) based extension of the i-vector approach, which allows i-vectors to be successfully applied to text-dependent speaker verification. In our approach, the Universal Background Model (UBM) for training phrase-independent i-vector extractor is based on a set of monophone HMMs instead of the standard Gaussian Mixture Model (GMM). To... 

Polystyrene is one of the best candidates as the extracting medium due to its high stability in different media and acceptable extraction capability. However, the hydrophobic nature and low wettability of polystyrene limits its application to non–polar analytes. To resolve this limitation, in this project, amine groups were chemically attached to the surface of magnetic polystyrene. The resulting hydrophilic magnetic particles were expected to be capable of extracting both polar and non–polar analytes. Non–steroidal anti–inflammatory drugs (NSAIDs) were chosen for testing the applicability of modified magnetic polystyrene according to the importance of their analysis and also their wide... 

Sample preparation for non-target analysis is challenging due to the difficulty in the extraction of polar and non-polar analytes simultaneously. Most commercial solid sorbents lack the proper comprehensiveness for extraction of analytes with different physiochemical properties. A possible key is the combination of hydrophobic polymer and hydrophilic surface functional groups in solid based extraction methods in order to generate the susceptibility for retaining both polar and non-polar analytes. To pursue this goal, in this study, four polar groups including [sbnd]NH 2 , [sbnd]NO 2 , [sbnd]COOH, and [sbnd]COCH 3 were chemically bound to Amberlite XAD-4 substrate in order to prepare a... 

Signature verification (SV) is one of the common methods for identity verification in banking, where for security reasons, it is very important to have an accurate method for automatic SV (ASV). ASV is usually addressed by comparing the test signature with the enrolment signature(s) signed by the individual whose identity is claimed in two manners: online and offline. In this study, a new method based on the i-vector is proposed for online SV. In the proposed method, a fixed-length vector, called i-vector, is extracted from each signature and then this vector is used for template making. Several techniques such as nuisance attribute projection (NAP) and within-class covariance normalisation... 

Cosine similarity and Probabilistic Linear Discriminant Analysis (PLDA) in i-vector space are two state-of-the-art scoring methods in speaker verification field. While PLDA usually gives better accuracy, Cosine Similarity Scoring (CSS) remains a widely used method due to simplicity and acceptable performance. In this domain, several channel compensation and score normalization methods have been proposed to improve the performance. We investigate non-speaker information in cosine similarity metric and propose a new approach to remove it from the decision making process. I-vectors hold a large amount of non-speaker information such as channel effects, language, and phonetic content. This type... 

Recently, a new data collection was initiated within the RedDots project in order to evaluate text-dependent and text-prompted speaker recognition technology on data from a wider speaker population and with more realistic noise, channel and phonetic variability. This paper analyses our systems built for RedDots challenge-the effort to collect and compare the initial results on this new evaluation data set obtained at different sites. We use our recently introduced HMM based i-vector approach, where, instead of the traditional GMM, a set of phone specific HMMs is used to collect the sufficient statistics for i-vector extraction. Our systems are trained in a completely phraseindependent way on... 

The final goal in a perforation operation is achieving the maximum production and reducing perforation damage, using optimal completion process. The Dynamic Underbalanced Perforation (DUP) as one of the more recent completion technologies minimizes or even eliminates the perforation crushed zone by optimizing the well's dynamic underbalance. Dynamic underbalance is a transient underbalance process that occurs immediately after creation of the perforation tunnels. The modeling of this process is essential in designing the optimal configuration of the perforation charges to evaluate the perforation efficiency. In this study we propose a novel and efficient numerical method, to optimize the... 

In this work, an efficient treatment strategy for hepatitis C disease using interferon (IFN) has been proposed on the basis of the back-stepping control technique. The basic model of the hepatitis C virus (HCV) has been considered for controller design. To tackle the problem of model parameter variations, the adaptive version of the back-stepping method has been utilized. For applying the proposed treatment, all states should be available while only the viral load is measured. To solve this problem, a nonlinear Luenberger-like observer has been designed to estimate the unmeasured states. In the proposed treatment, limitation of the drug efficacy has been taken into account. Asymptotical... 

In this work, design of an observer-based nonlinear controller for a class of single input-single output (SISO) systems in the general strict feedback form subject to input saturation based on the back-stepping technique has been addressed. A full order adaptive observer is constructed to estimate the unknown states and system parameters simultaneously. The proposed control scheme is singularity free and can handle the input nonlinearity. Asymptotical stability of the closed-loop system in the presence of observer dynamics and input saturation has been established by the Lyapunov stability theorem. The effectiveness of the proposed controller is illustrated by applying the proposed scheme to...