{"title":"Aspects In Modeling And Real-time Synthesis Of The Acoustic Guitar","authors":"M. Karjalainen, U. Laine, V. Valimaki","doi":"10.1109/ASPAA.1991.634150","DOIUrl":null,"url":null,"abstract":"This paper will address the problem of modeling the acoustic guitar for real-time synthesis on signal processairs. We will present a scheme for modeling the string for high-quality sound synthesis when the length of Ihe string is changing dynamically. We will focus also on the problem of modeling the body of the guitar for real-time synthesis. Filter-based approaches were experimented by LPC estimation, IIR-filter synthesis and FIR-filter approximation. Perceptual evaluation was used and taken into account. Real-time synthesis was implemented on the TMS32OC30 floating-point signal processor. The presentation includes audio examples. Introduction Computational modeling of musical instruments is an alternative to commonly used and more straightforward sound synthesis techniques like FA4 synthesis and waveform sampling. The traditional,approach 10 efficient modeling of a vibrating string has been to use proper digital filters or transmission lines, see e.g. Kauplus and Strong [l] and its extensions by Jaffe and Smith [2]. These represent \"semiphysical\" modeling where only some of the most fundamental features of the string, especially the transmission line property, are retained to achieve efficient computation. More complete finite element models and other kinds of physical modeling may lead to very realistic sounds but tend to be computationally too expensive for real-time purposes. Modeling of the guitar body for real-time sound synthesis seems too difficult unless a digital filter approach to approximate the transfer function is used. The derivation of the detailed transfer function from mechanical and acoustical parameters seems impossible. The remaining choice is to estimate the transfer function filter from measurements of a real guitar or to design a filter that approximates the general properties of the real guiltar body. In addition to strings and body the interactions between them (at least between the strings) should be included. String Modeling The natural way of modeling a guitar string is to describe it as a two-directional transmission or delay line (see Fig. la.) where the vibrational waves travel in both directions, reflecting at both ends. If all losses and other nonidealities are reduced to the reflection filters at the end points the computation of the ideal string is efficient by using two delay lines. The next problem is how to approximate the fractional part of the delay to achieve any (non-integer) length of the delay Wine. Allpass filters [2] are considered as a good solution if the string length is fixed. If the length is dynamically varying, however, it is very difficult to avoid transients and glitches when Ihe integer part of the delay line must change its length. E x c i t a t i d po in t","PeriodicalId":146017,"journal":{"name":"Final Program and Paper Summaries 1991 IEEE ASSP Workshop on Applications of Signal Processing to Audio and Acoustics","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Final Program and Paper Summaries 1991 IEEE ASSP Workshop on Applications of Signal Processing to Audio and Acoustics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASPAA.1991.634150","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
This paper will address the problem of modeling the acoustic guitar for real-time synthesis on signal processairs. We will present a scheme for modeling the string for high-quality sound synthesis when the length of Ihe string is changing dynamically. We will focus also on the problem of modeling the body of the guitar for real-time synthesis. Filter-based approaches were experimented by LPC estimation, IIR-filter synthesis and FIR-filter approximation. Perceptual evaluation was used and taken into account. Real-time synthesis was implemented on the TMS32OC30 floating-point signal processor. The presentation includes audio examples. Introduction Computational modeling of musical instruments is an alternative to commonly used and more straightforward sound synthesis techniques like FA4 synthesis and waveform sampling. The traditional,approach 10 efficient modeling of a vibrating string has been to use proper digital filters or transmission lines, see e.g. Kauplus and Strong [l] and its extensions by Jaffe and Smith [2]. These represent "semiphysical" modeling where only some of the most fundamental features of the string, especially the transmission line property, are retained to achieve efficient computation. More complete finite element models and other kinds of physical modeling may lead to very realistic sounds but tend to be computationally too expensive for real-time purposes. Modeling of the guitar body for real-time sound synthesis seems too difficult unless a digital filter approach to approximate the transfer function is used. The derivation of the detailed transfer function from mechanical and acoustical parameters seems impossible. The remaining choice is to estimate the transfer function filter from measurements of a real guitar or to design a filter that approximates the general properties of the real guiltar body. In addition to strings and body the interactions between them (at least between the strings) should be included. String Modeling The natural way of modeling a guitar string is to describe it as a two-directional transmission or delay line (see Fig. la.) where the vibrational waves travel in both directions, reflecting at both ends. If all losses and other nonidealities are reduced to the reflection filters at the end points the computation of the ideal string is efficient by using two delay lines. The next problem is how to approximate the fractional part of the delay to achieve any (non-integer) length of the delay Wine. Allpass filters [2] are considered as a good solution if the string length is fixed. If the length is dynamically varying, however, it is very difficult to avoid transients and glitches when Ihe integer part of the delay line must change its length. E x c i t a t i d po in t