Voice Based Database Management System Using DSP Processor

Security is provided to customers through PIN/ID protection, to secure their data and information using password. This method require user to authenticate them by entering password. There are cases of fraud and theft when people can easily know the password. But there is a existing technology known as Bio-metric Identification System. It uses an individual's bio-metric characteristics, that is unique and therefore can be used to authenticate the user authority access. This invention is an implementation of speaker verification for attendance monitoring system using DSP Processor. First, speech signal will go to pre-processing phase, where it will remove the background noise then, speech signal's features will be extracted using Mel Frequency Cepstral Coefficients (MFCC) method. Then, using Hamming Window, the features will be matched with the reference speech in database. The speaker is identified by comparing the speech signal from the tested speaker. The main focus of this invention is speaker verification, which is compared between speech signal from unknown speaker to a database of known speaker using utterances. The speaker identification is used in this invention for creating database and identifying the students for maintaining attendance record. LCD Display is interfaced with Processor to show the presence of the students for a particular subject. So this can be used for monitoring the attendance of students. Also defaulter student’s list is find out according to the criteria, and it is maintained in MS Excel sheet. Future scope for this can be, informing the monthly attendance to their parents through a text message on their mobile phones using a GSM Module interfaced to processor. DOI: 10.17762/ijritcc2321-8169.150511

Homomorphic Encryption for Speaker Recognition: Protection of Biometric Templates and Vendor Model Parameters

Data privacy is crucial when dealing with biometric data. Accounting for the latest European data privacy regulation and payment service directive, biometric template protection is essential for any commercial application. Ensuring unlinkability across biometric service operators, irreversibility of leaked encrypted templates, and renewability of e.g., voice models following the i-vector paradigm, biometric voice-based systems are prepared for the latest EU data privacy legislation. Employing Paillier cryptosystems, Euclidean and cosine comparators are known to ensure data privacy demands, without loss of discrimination nor calibration performance. Bridging gaps from template protection to speaker recognition, two architectures are proposed for the two-covariance comparator, serving as a generative model in this study. The first architecture preserves privacy of biometric data capture subjects. In the second architecture, model parameters of the comparator are encrypted as well, such that biometric service providers can supply the same comparison modules employing different key pairs to multiple biometric service operators. An experimental proof-of-concept and complexity analysis is carried out on the data from the 2013-2014 NIST i-vector machine learning challenge

Effectiveness in the Realisation of Speaker Authentication

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.An important consideration for the deployment of speaker recognition in authentication applications is the approach to the formation of training and testing utterances . Whilst defining this for a specific scenario is influenced by the associated requirements and conditions, the process can be further guided through the establishment of the relative usefulness of alternative frameworks for composing the training and testing material. In this regard, the present paper provides an analysis of the effects, on the speaker recognition accuracy, of various bases for the formation of the training and testing data. The experimental investigations are conducted based on the use of digit utterances taken from the XM2VTS database. The paper presents a detailed description of the individual approaches considered and discusses the experimental results obtained in different cases

Identity in research infrastructure and scientific communication: Report from the 1st IRISC workshop, Helsinki Sep 12-13, 2011

Motivation for the IRISC workshop came from the observation that identity and digital identification are increasingly important factors in modern scientific research, especially with the now near-ubiquitous use of the Internet as a global medium for dissemination and debate of scientific knowledge and data, and as a platform for scientific collaborations and large-scale e-science activities.

The 1 1/2 day IRISC2011 workshop sought to explore a series of interrelated topics under two main themes: i) unambiguously identifying authors/creators & attributing their scholarly works, and ii) individual identification and access management in the context of identity federations. Specific aims of the workshop included:

• Raising overall awareness of key technical and non-technical challenges, opportunities and developments.
• Facilitating a dialogue, cross-pollination of ideas, collaboration and coordination between diverse – and largely unconnected – communities.
• Identifying & discussing existing/emerging technologies, best practices and requirements for researcher identification.

This report provides background information on key identification-related concepts & projects, describes workshop proceedings and summarizes key workshop findings