Impulse Response Modeling of the Box Shaped Acoustic Guitar

Minakshi Pradeep Atre, S. Apte
{"title":"Impulse Response Modeling of the Box Shaped Acoustic Guitar","authors":"Minakshi Pradeep Atre, S. Apte","doi":"10.5772/intechopen.99757","DOIUrl":null,"url":null,"abstract":"Music is the pulse of human lives and is an amazing tool to relieve and re-live. And when it comes to the signal processing, impulse is the pulse of the researchers. The work presented here is focused on impulse response modeling of noted produced by box shaped acoustic guitar. The impulse response is very fundamental behavior of any system. The music note is the convolution of the impulse response and the excitation signal of that guitar. The frequency of the generated music note follows the octave rule. The octave rule can be checked for impulse responses as well. If the excitation signal and impulse response are separated, then an impulse response of a single fret can be used to generate the impulse responses of other frets. Here the music notes are analyzed and synthesized on the basis of the plucking style and plucking expression of the guitar-player. If the impulse response of the musical instrument is known, the output music note can be synthesized in an unusual manner. Researchers have been able to estimate the impulse response by breaking the string of the guitar. Estimating the impulse response from the recorded music notes is possible using the methodology of cepstral domain window. By means of the Adaptive Cepstral Domain Window (ACDW) the author estimated the impulse response of guitar notes. The work has been further extended towards the classification of synthesized notes for plucking style and plucking expression using Neural Network and Machine Learning algorithms.","PeriodicalId":206389,"journal":{"name":"Music in Health and Diseases [Working Title]","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Music in Health and Diseases [Working Title]","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5772/intechopen.99757","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Music is the pulse of human lives and is an amazing tool to relieve and re-live. And when it comes to the signal processing, impulse is the pulse of the researchers. The work presented here is focused on impulse response modeling of noted produced by box shaped acoustic guitar. The impulse response is very fundamental behavior of any system. The music note is the convolution of the impulse response and the excitation signal of that guitar. The frequency of the generated music note follows the octave rule. The octave rule can be checked for impulse responses as well. If the excitation signal and impulse response are separated, then an impulse response of a single fret can be used to generate the impulse responses of other frets. Here the music notes are analyzed and synthesized on the basis of the plucking style and plucking expression of the guitar-player. If the impulse response of the musical instrument is known, the output music note can be synthesized in an unusual manner. Researchers have been able to estimate the impulse response by breaking the string of the guitar. Estimating the impulse response from the recorded music notes is possible using the methodology of cepstral domain window. By means of the Adaptive Cepstral Domain Window (ACDW) the author estimated the impulse response of guitar notes. The work has been further extended towards the classification of synthesized notes for plucking style and plucking expression using Neural Network and Machine Learning algorithms.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
箱形原声吉他的脉冲响应建模
音乐是人类生命的脉搏,是一种神奇的放松和重新生活的工具。当涉及到信号处理时,脉冲是研究人员的脉搏。本文研究的是箱形原声吉他产生音符的脉冲响应模型。脉冲响应是任何系统的基本行为。音符是吉他的脉冲响应和激励信号的卷积。生成的音符的频率遵循八度规则。八度规则也可以检查脉冲响应。如果将激励信号和脉冲响应分离,则可以使用单个频点的脉冲响应来产生其他频点的脉冲响应。这里根据吉他手的拨弦风格和拨弦表现对音符进行分析和合成。如果乐器的脉冲响应是已知的,输出音符可以合成在一个不寻常的方式。研究人员已经能够通过打断吉他的弦来估计脉冲响应。利用倒谱域窗的方法可以从记录的音符中估计脉冲响应。利用自适应倒谱域窗(ACDW)估计了吉他音符的脉冲响应。这项工作已经进一步扩展到使用神经网络和机器学习算法对采摘风格和采摘表达的合成音符进行分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Multivariate Approach to Reading Comprehension and Sight-Reading Impulse Response Modeling of the Box Shaped Acoustic Guitar The Effects of Music Therapy on Cortisol Levels as a Biomarker of Stress in Children Music Therapy in Medicine of Islamic Civilisation Classic and Traditional Music Role in Cognitive Function and Critically Ill Patients
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1