A hidden Markov Model (hmm) based speaker identification system using mobile phone database of North Atlantic Treaty Organization (nato) words
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A Hidden Markov Model (HMM) based speaker identification system using mobile phone database of North Atlantic Treaty Organization (NATO) words Shyam S. Agrawal , Shweta Bansal , Dipti Pandey , et al. Citation: Proc. Mtgs. Acoust. 19, 060019 (2013); doi: 10.1121/1.4800721 View online: https://doi.org/10.1121/1.4800721 View Table of Contents: https://asa.scitation.org/toc/pma/19/1 Published by the Acoustical Society of America ARTICLES YOU MAY BE INTERESTED IN On the limits of automatic speaker verification: Explaining degraded recognizer scores through acoustic changes resulting from voice disguise The Journal of the Acoustical Society of America 146, 693 (2019); https://doi.org/10.1121/1.5119240 Hidden Markov and Gaussian mixture models for automatic call classification The Journal of the Acoustical Society of America 125, EL221 (2009); https://doi.org/10.1121/1.3124659 A Hidden Markov Model based speaker identification system using mobile phone database of North Atlantic Treaty Organization words The Journal of the Acoustical Society of America 133, 3247 (2013); https://doi.org/10.1121/1.4805213 Proceedings of Meetings on Acoustics Volume 19, 2013 http://acousticalsociety.org/ ICA 2013 Montreal Montreal, Canada 2 - 7 June 2013 Speech Communication Session 1aSCb: Digital Speech Processing (Poster Session) 1aSCb14. A Hidden Markov Model (HMM) based speaker identification system using mobile phone database of North Atlantic Treaty Organization (NATO) words Shyam S. Agrawal*, Shweta Bansal, Dipti Pandey and Himanshu Tayal *Corresponding author's address: Electronics & Communication, KIIT College of Engineering, Maruti Kunj, Near Bhondsi, Gurgaon, 122102, Haryana, India, dr.shyamsagrawal@gmail.com This paper describes results of an experiment to conduct Text Independent Speaker Identification of large number of speakers (about 100) using a standard vocabulary of about 23 NATO words- such as Alfa, Bravo, etc. These words in isolation were spoken in a sound treated room by Hindi natives having very good education in English ( both male and female) and recorded by a three channel data recording system-the cardioid microphone, electret condenser microphone and a NOKIA mobile telephone. The pre-processed digitized database of isolated words was further processed to determine 39 MFCC's and their derivatives and used to build an HMM model for each speaker based on all the words. The HMM model was trained using an HTK tool kit to generate the model parameters and tested using Viterbi algorithm. The identification of speakers was done in a closed set manner, based on comparison of each NATO word in the model. In addition to correct identification, false acceptance and false rejection scores were also found. The results show varying performance due to variations in channels, male/female speakers. The overall identification scores vary between 60% to 70% .The paper gives detailed analysis of results. Published by the Acoustical Society of America through the American Institute of Physics Download 247.06 Kb. Do'stlaringiz bilan baham: |
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