V. Vijay Anand ¹, C. Vijaya Banu ¹, V. Badrinath ¹, R. Veena ¹, K. Sowmiyaa ¹, S. Muthulakshmi ¹

Affiliations
1 School of Management, SASTRA University, Thanjavur - 613401, Tamil Nadu, IN

Abstract

Background/Objectives: Employee Engagement is an important factor in the organization to achieve the success and increase its productivity. EE is the key variable that brings employee and the management closer. There are many factors that influence Employee Engagement along with demographic factors. The researchers have identified some of variables and were grouped into a factor as Individual factor. Objectives: To study the relationship between demographic variables of the respondents and Employee Engagement; To understand the variation between the individual factors and Employee Engagement of bank employees; To study the effect of individual factors on Employee Engagement; To study the relationship between Employee Engagement and discretionary efforts as outcome variable and to understand the effect of Employee Engagement and retention as outcome variable. Methods/Statistical Analysis: 124 samples have been taken for this study and the statistical tools such as chi-square test, ANOVA and Regression were used for analysis. Findings: There is positive relationship between the factors viz. organizational and group factors with Employee Engagement. These factors are to be taken care and more importance for better performance. In addition to that, more involvement of employees is required to have better productivity in the organization. Applications/Improvements: The current study analyzes the factors influencing the Employee Engagement of the employees from rural areas and the key findings of the study will help banking organisation in rural areas to formulate HR policies which in turn promotes their engagement level.

Keywords

Discretionary Effort, Employee Engagement, Growth and Development, Productivity, Role Clarity.

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Bhanuprathap Kari ¹, S. Muthulakshmi ¹

Affiliations
1 School of Electronics Engineering, VIT University, Chennai-600127, Tamil Nadu, IN

Abstract

Background: Speaker recognition systems plays a pivotal role in the field of forensics, security and biometric authentication for verifying or identifying the speaker from the group of speakers. Methods: This paper gives a brief introduction about developing a hardware based speaker recognition system using Mel Frequency Cepstral Coefficients (MFCC) which are extracted from input speech signal to linearize the frequency scale at higher frequencies and Perceptron Neural Networks to provide layer weights for verifying the speaker identity to compare the output in the database of stored speaker identities. Findings: The input speech features are extracted using blocking and windowing to reduce noise and get the audio samples to store in the RAM where sampled data is converted into frequency domain using FFT to get the Cepstral Coefficients which are normalised and fed to neural network tool box present in the MATLAB to obtain layer weights for given set of data and the output is compared with the saved speaker identities to find a match. The decision making logic is written in NIOS II processor of FPGA where the taken input features are compared to the existing database of speaker identities with the help of perceptron neural network layer weights which gives the nearest possibility of the match in the database of the group of speakers. The designed system has been tested using two speakers as reference where the vowels spoken by them are taken into account to compare with the database of speakers already stored in FPGA. Conclusion/ Improvements: The probability of detection of the speakers is 80% and verifying the speaker is quite accurate in hardware based systems than in software based systems where performance factor is less. The given performance in the designed system can be increased by retraining the neural networks which can provide nearly 90% in detecting the speaker.

Keywords

Artificial Neural Networks, FPGA, MFCC, NIOS II, Speaker Recognition

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