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: Warped Linear Prediction of Physical Model Excitations with Applications in Audio Compression and Instrument Synthesis | EURASIP Journal on Applied Signal Processing 2004 7 1036-1044 2004 Hindawi Publishing Corporation Warped Linear Prediction of Physical Model Excitations with Applications in Audio Compression and Instrument Synthesis Alexis Glass Department of Acoustic Design Graduate School of Design Kyushu University 4-9-1 Shiobaru Minami-ku Fukuoka 815-8540 Japan Email alexis@ Kimitoshi Fukudome Department of Acoustic Design Faculty of Design Kyushu University 4-9-1 Shiobaru Minami-ku Fukuoka 815-8540 Japan Email fukudome@ Received 8 July 2003 Revised 13 December 2003 A sound recording of a plucked string instrument is encoded and resynthesized using two stages of prediction. In the first stage of prediction a simple physical model of a plucked string is estimated and the instrument excitation is obtained. The second stage of prediction compensates for the simplicity of the model in the first stage by encoding either the instrument excitation or the model error using warped linear prediction. These two methods of compensation are compared with each other and to the case of single-stage warped linear prediction adjustments are introduced and their applications to instrument synthesis and MPEG4 s audio compression within the structured audio format are discussed. Keywords and phrases warped linear prediction audio compression structured audio physical modelling sound synthesis. 1. INTRODUCTION Since the discovery of the Karplus-Strong algorithm 1 and its subsequent reformulation as a physical model of a string a subset of the digital waveguide 2 physical modelling has seen the rapid development of increasingly accurate and disparate instrument models. Not limited to string model implementations of the digital waveguide such as the kantele 3 and the clavichord 4 models for brass woodwind and percussive instruments have made physical modelling ubiquitous. With the increasingly complex models however the task of parameter selection .
