This study is mainly focusing on the problem of spacecraft close-range proximity with obstacle avoidance in presence complex shape. A novel Gaussian mixture model–based nonsingular terminal sliding mode control (GMM-NTSMC) proposed. achieved by developing GMM-based potential function a switching surface NTSMC. It theoretically proved that closed-loop system globally stable. The main contributio...

1 Introduction This report presents a novel speaker verification system that generates a new feature set that captures long duration speaker identifying characteristics while taking advantage of the well-established and well-studied Gaussian Mixture Model system (GMM). Much of the innovation in the system is contained in the intelligent exploitation of traditional cepstral features such that te...

This paper introduces the performance evaluation of statististical approaches for Automatic-text-independent Speaker Recognition system. Automatic-text-independent Speaker Recognition system is to quickly and accurately identify the person from his/her voice. The study on the effect of feature vector size for good speaker recognition demonstrates that the feature vector size in the range of 18-...

We describe a simple, novel, and efficient system for speaker comparison with two main components. First, the system uses a new approximate KL divergence distance extending earlier GMM parameter vector SVM kernels. The approximate distance incorporates data-dependent mixture weights as well as the standard MAP-adapted GMM mean parameters. Second, the system applies a weighted nuisance projectio...

Speaker verification is the process of accepting or rejecting claimed identity in terms of its sound features. A speaker verification system can be used for numerous security systems, including bank account accessing, getting to security points, criminology and etc. When a speaker verification system wants to check the identity of individuals remotely, it confronts problems such as noise effect...

We propose an approach to reverberant speech recognition adopting deep learning in front end as well as back end of the system. At the front end, we adopt a deep autoencoder for enhancing the speech feature parameters, and the recognition is performed using a DNN-HMM acoustic models trained on multi-condition data. The system was evaluated through the ASR task in Chime Challenge 2014. The DNN-H...

This study was conducted to investigate the determinants of bank’s stability in an emerging country. Data were collected from commercial banks listed on Vietnam’s Stock Exchanges over years...

In this paper, we present the use of Gaussian Supervectors with Support Vector Machines classifiers (GSV-SVM) in an acoustic speaker diarization and a speaker tracking system, compared with a standard Gaussian Mixture Model system based on adapted Universal Background Models (GMM-UBM). GSVSVM systems (which share the adaptation step with the GMMUBM systems) are observed to have comparable perfo...

This paper focuss speaker identity verification system from the Department of Electronic Engineering, Tsinghua University (THUEE) for Evalita 2009 Speaker Identity Verification Application Track (SIV-A). Two systems are submitted for the evaluation. The primary one consists of GMM-UBM and GMM-SVM. The contrast one is based on high level feature. We describe each subsystem briefly and give their...

We compared the performances of two procedures for calculating the likelihood ratio (LR) on the same set of text data. The first procedure was a multivariate kernel density (MVKD) procedure which has been successfully applied to various types of forensic evidence, including glass fragments, handwriting, fingerprint, voice, and texts. The second procedure was a Gaussian mixture model – universal...