Đang chuẩn bị nút TẢI XUỐNG, xin hãy chờ
Tải xuống
Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học Journal of Biology đề tài: Research Article Employing Second-Order Circular Suprasegmental Hidden Markov Models to Enhance Speaker Identification Performance in Shouted Talking Environments | Hindawi Publishing Corporation EURASIP Journal on Audio Speech and Music Processing Volume 2010 Article ID 862138 10 pages doi 10.1155 2010 862138 Research Article Employing Second-Order Circular Suprasegmental Hidden Markov Models to Enhance Speaker Identification Performance in Shouted Talking Environments Ismail Shahin Electrical and Computer Engineering Department University of Sharjah P.O. Box 27272 Sharjah United Arab Emirates Correspondence should be addressed to Ismail Shahin ismail@sharjah.ac.ae Received 8 November 2009 Accepted 18 May 2010 Academic Editor Yves Laprie Copyright 2010 Ismail Shahin. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Speaker identification performance is almost perfect in neutral talking environments. However the performance is deteriorated significantly in shouted talking environments. This work is devoted to proposing implementing and evaluating new models called Second-Order Circular Suprasegmental Hidden Markov Models CSPHMM2s to alleviate the deteriorated performance in the shouted talking environments. These proposed models possess the characteristics of both Circular Suprasegmental Hidden Markov Models CSPHMMs and Second-Order Suprasegmental Hidden Markov Models SPHMM2s . The results of this work show that CSPHMM2s outperform each of First-Order Left-to-Right Suprasegmental Hidden Markov Models LTRSPHMM1s Second-Order Left-to-Right Suprasegmental Hidden Markov Models LTRSPHMM2s and First-Order Circular Suprasegmental Hidden Markov Models CSPHMM1s in the shouted talking environments. In such talking environments and using our collected speech database average speaker identification performance based on LTRSPHMM1s LTRSPHMM2s CSPHMM1s and CSPHMM2s is 74.6 78.4 78.7 and 83.4 respectively. Speaker identification performance obtained based on CSPHMM2s is close to that
