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In this paper, we propose text independent speaker identification with a finite multivariate generalised Gaussian Mixture Model (GMM) with a k-means algorithm. Each speaker's speech spectra are characterised with a mixture of generalised Gaussian distribution that includes Gaussian and Laplacian distribution as a particular case. Speech analysis is done with the Mel Frequency Cepstral Coefficients (MFCC) extracted from the front end process. Using the EM algorithm and k-means algorithm the model parameters the numbers of acoustic classes associated with each speech spectra are Determined . The performance of the proposed algorithm is studied through experimental evaluation and observed that this algorithm outperforms the existing speaker identification algorithm with GMM. It is also observed that this algorithm performs efficiently even with a heterogeneous population with small (less than 2 seconds) utterances.Keywords: gaussian mixture model; GMM; generalised gaussian mixture model; MFCC; mel frequency cepstral coefficients; k-means clustering; EM algorithm and speech analysis.Reference to this paper should be made as follows: Sailaja, V., Srinivasa Rao, K. and Reddy, K.V.V.S. (2013) 'Text independent speaker identification with finite multivariate generalised Gaussian mixture model and k-means algorithm', Int.

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Just as it is impossible to know when a swimming fish will drink water, so it is impossible to find out when a corporate steward is stealing money" From Kautilya'sArthashastra (300 B.C) Cadbury (1992) defines corporate governance as the "whole system of controls both financial and otherwise by which a company is directed and controlled". In simple words it is all about promoting corporate fairness, transparency and accountability. The opening of the economy has brought growth opportunities with improved competitiveness this has also given rise to cut throat competition in all sectors, which has tempted managers to adopt practices which at times dilute the ethical norms. This competition has put the onus on managers to show improvement in performances quarter by quarter persuading them to tamper with some of the best practices in the rat race for market share growth rate, visibility in securities market. The structure to ensure corporate governance includes the board of directors, top management, shareholders, creditors and all other stakeholders. Frauds in corporate governance According to KPMG fraud survey, organizations are reporting more experiences of fraud than prior years and are taking actions to deal with it. Seventy five percent of companies surveyed reports that they experienced increasing instances of fraud. While employee fraud is the most prevalent type of fraud experienced by organizations, financial reporting fraud and medical insurance fraud are the most costly. During the recent past the financial frauds are almost doubled. Organizations have taken reactive and preventive measures in controlling the corporate frauds like internal audit, internal controls, and notifications by an employee are the three ways of uncovering fraud. The present paper is an exploratory study that focuses on various corporate frauds, genesis of the frauds, people responsible for various frauds and the role of regulatory bodies in overcoming those frauds.