Multi Objective Optimization Problem resolution based on Hybrid Ant-Bee Colony for Text Independent Speaker Verification

Today major section of automatic speaker verification (ASV) research is focused on multiple objectives like optimization of feature subset and minimization of Equal Error Rate (EER). As such, numerous systems for feature dimension reduction are proposed. This includes framework coaching and testing analysis for every feature set that could be a time esurient trip. Because of its significance, the issue of feature selection has been researched by numerous scientists. In this paper, a new feature subset selection procedure is presented. Hybrid of Ant Colony and Artificial Bee Colony optimized the feature subset over 85% thereby decreased the computational complexity of ASV. Additionally an external record is maintained to store non-dominated solution vectors for which concept of Pareto dominance is used. An overall optimization of 87% is achieved thereby improved the recognition rate of ASV.

[1]  Abed Heshmati,et al.  Highly Efficient Dimension Reduction for Text-Independent Speaker Verification Based on Relieff Algorithm and Support Vector Machines , 2013 .

[2]  Steven van de Par,et al.  Noise-Robust Speaker Recognition Combining Missing Data Techniques and Universal Background Modeling , 2012, IEEE Transactions on Audio, Speech, and Language Processing.

[3]  Shunmugapriya Palanisamy.  Artificial Bee Colony Approach for Optimizing Feature Selection , 2012 .

[4]  Shin-ichi Sato,et al.  Speaker recognition analysis using running autocorrelation function parameters. , 2013 .

[5]  Haizhou Li,et al.  TEXT-INDEPENDENT SPEAKER RECOGNITION , 2011 .

[6]  Carlos A. Coello Coello,et al.  Multi-Objective Ant Colony Optimization: A Taxonomy and Review of Approaches , 2011, Integration of Swarm Intelligence and Artificial Neural Network.

[7]  N. Murali Krishna,et al.  Emotion Recognition using Dynamic Time Warping Technique for Isolated Words , 2011 .

[8]  Zhihua Cui,et al.  Swarm Intelligence and Bio-Inspired Computation: Theory and Applications , 2013 .

[9]  Alex Alves Freitas,et al.  Data mining with an ant colony optimization algorithm , 2002, IEEE Trans. Evol. Comput..

[10]  Wen Wang,et al.  Automatic Detection of Speaker Attributes Based on Utterance Text , 2011, INTERSPEECH.

[11]  Roberto Montemanni,et al.  A new algorithm for a Dynamic Vehicle Routing Problem based on Ant Colony System , 2002 .

[12]  Dervis Karaboga,et al.  A comparative study of Artificial Bee Colony algorithm , 2009, Appl. Math. Comput..

[13]  Janice I. Glasgow,et al.  Swarm Intelligence: Concepts, Models and Applications , 2012 .

[14]  Shawki Areibi,et al.  Strength Pareto Particle Swarm Optimization and Hybrid EA-PSO for Multi-Objective Optimization , 2010, Evolutionary Computation.

[15]  S Kanmani,et al.  Artificial Bee Colony Approach for Approach for Approach for Approach for Optimizing Feature Selection , 2012 .

[16]  Hanning Chen,et al.  Solving Multiobjective Optimization Problems Using Artificial Bee Colony Algorithm , 2011 .

[17]  Sudhanshu Prakash Tiwari,et al.  Travelling Salesman Problem Using Bee Colony With SPV , 2012 .

[18]  Özgür B. Akan,et al.  A survey on bio-inspired networking , 2010, Comput. Networks.

[19]  John H. L. Hansen,et al.  An investigation on back-end for speaker recognition in multi-session enrollment , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

[20]  Song Zheng,et al.  Ant Colony Optimization based on Pheromone Trail Centralization , 2006, 2006 6th World Congress on Intelligent Control and Automation.

[21]  Hong Tat Ewe,et al.  Ant Colony Optimization Approaches to the Degree-constrained Minimum Spanning Tree Problem , 2008, J. Inf. Sci. Eng..

[22]  Haizhou Li,et al.  Low-Variance Multitaper MFCC Features: A Case Study in Robust Speaker Verification , 2012, IEEE Transactions on Audio, Speech, and Language Processing.

[23]  Monica Sood,et al.  Speaker Recognition Based On Cuckoo Search Algorithm , 2013 .

[24]  Francisco Herrera,et al.  A taxonomy and an empirical analysis of multiple objective ant colony optimization algorithms for the bi-criteria TSP , 2007, Eur. J. Oper. Res..

[25]  Balaji Vasan Srinivasan,et al.  A partial least squares framework for speaker recognition , 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[26]  DresslerFalko,et al.  A survey on bio-inspired networking , 2010 .

[27]  Khalid Saeed,et al.  A Speech-and-Speaker Identification System: Feature Extraction, Description, and Classification of Speech-Signal Image , 2007, IEEE Transactions on Industrial Electronics.

[28]  Balaji Vasan Srinivasan,et al.  A Symmetric Kernel Partial Least Squares Framework for Speaker Recognition , 2013, IEEE Transactions on Audio, Speech, and Language Processing.

[29]  J. S. Devi,et al.  Speaker Emotion Recognition based on Speech Features and Classification Techniques , 2014 .

[30]  Dervis Karaboga,et al.  A novel clustering approach: Artificial Bee Colony (ABC) algorithm , 2011, Appl. Soft Comput..

[31]  Marco Dorigo,et al.  AntNet: Distributed Stigmergetic Control for Communications Networks , 1998, J. Artif. Intell. Res..

[32]  Frank Neumann,et al.  Ant Colony Optimization and the minimum spanning tree problem , 2006, Theor. Comput. Sci..

[33]  Sandeep Kumar,et al.  Improved Onlooker Bee Phase in Artificial Bee Colony Algorithm , 2014, ArXiv.

[34]  Siva Prasad Nandyala,et al.  Automatic Speech Emotion and Speaker Recognition Based on Hybrid GMM and FFBNN , 2014 .

[35]  Shingo Kuroiwa,et al.  Speaker Recognition for Wire/Wireless Communication Systems , 2006, Int. Arab J. Inf. Technol..

[36]  Mohammad Davarpanah Jazi,et al.  Text-independent speaker verification using ant colony optimization-based selected features , 2011, Expert Syst. Appl..

[37]  John H. L. Hansen,et al.  Acoustic Factor Analysis for Robust Speaker Verification , 2013, IEEE Transactions on Audio, Speech, and Language Processing.

[38]  Ashu Bansal,et al.  Speaker Recognition Using MFCC Front End Analysis and VQ Modeling Technique for Hindi Words using MATLAB , 2012 .

[39]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[40]  Janusz Bobulski.  Text-independent speaker recognition , 2007 .