@article{(Open Science Index):https://publications.waset.org/pdf/9996651,
	  title     = {Evaluation of Features Extraction Algorithms for a Real-Time Isolated Word Recognition System},
	  author    = {Tomyslav Sledevič and  Artūras Serackis and  Gintautas Tamulevičius and  Dalius Navakauskas},
	  country	= {},
	  institution	= {},
	  abstract     = {Paper presents an comparative evaluation of features extraction algorithm for a real-time isolated word recognition system
based on FPGA. The Mel-frequency cepstral, linear frequency cepstral, linear predictive and their cepstral coefficients were
implemented in hardware/software design. The proposed system was investigated in speaker dependent mode for 100 different
Lithuanian words. The robustness of features extraction algorithms was tested recognizing the speech records at different signal to noise rates. The experiments on clean records show highest accuracy for Mel-frequency cepstral and linear frequency cepstral coefficients. For records with 15 dB signal to noise rate the linear predictive cepstral coefficients gives best result. The hard and soft part of the system is clocked on 50 MHz and 100 MHz accordingly. For the classification purpose the pipelined dynamic time warping core was implemented. The proposed word recognition system satisfy the real-time requirements and is suitable for applications in embedded systems.
},
	    journal   = {International Journal of Computer and Systems Engineering},
	  volume    = {7},
	  number    = {12},
	  year      = {2013},
	  pages     = {1589 - 1593},
	  ee        = {https://publications.waset.org/pdf/9996651},
	  url   	= {https://publications.waset.org/vol/84},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 84, 2013},
	}