tailieunhanh - báo cáo hóa học:" DWT and LPC based feature extraction methods for isolated word recognition"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: DWT and LPC based feature extraction methods for isolated word recognition | EURASIP Journal on Audio Speech and Music Processing SpringerOpen0 This Provisional PDF corresponds to the article as it appeared upon acceptance. Fully formatted PDF and full text HTML versions will be made available soon. DWT and LPC based feature extraction methods for isolated word recognition EURASIP Journal on Audio Speech and Music Processing 2012 2012 7 doi 1687-4722-2012-7 Navnath S Nehe nsnehe@ Raghunath S Holambe rsholambe@ ISSN 1687-4722 Article type Research Submission date 21 January 2011 Acceptance date 30 January 2012 Publication date 30 January 2012 Article URL http content 2012 1 7 This peer-reviewed article was published immediately upon acceptance. It can be downloaded printed and distributed freely for any purposes see copyright notice below . For information about publishing your research in EURASIP ASMP go to http authors instructions For information about other SpringerOpen publications go to http 2012 Nehe and Holambe licensee Springer. This is an open access article distributed under the terms of the Creative Commons Attribution License http licenses by which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. DWT and LPC based feature extraction methods for isolated word recognition Navnath S Nehe 1 and Raghunath S Holambe2 Department of Instrumentation Engineering Pravara Rural Engineering College Loni 413736 Maharashtra India . Institute Engineering Technology Vishnupuri Nanded Maharashtra India Corresponding author nsnehe@ Email address RSH rsholambe@ Abstract In this article new feature extraction methods which utilize wavelet decomposition and reduced order linear predictive coding LPC coefficients have been proposed for speech recognition. The coefficients have been derived from the speech frames decomposed using discrete .