声音合成工具使用吉他弦与振荡方法进行练习

Andreas Febrillianto Primawan, Yohannes Suyanto, Catur Atmaji
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引用次数: 0

摘要

Gamelan是印度尼西亚的传统乐器,经常用于传统活动和派对。社区对gamelan的需求实际上已经增加,但不幸的是gamelan价格非常昂贵,gamelan本身很难从一个地方移动到另一个地方。除此之外,伽美兰可以演奏的有限音调降低了公众对演奏这种乐器的兴趣。当前的技术发展使得用几种方法进行语音合成成为可能。可以使用的一种方法是变桨。这项研究的目的是在拨动吉他弦的基础上产生一种合成的沙隆音。在频域中对沙隆声音信号进行分析,以获得合成过程中所需的半音值。合成沙隆信号生成是通过调用以soundfont形式存储的合成沙隆声音,以及从吉他输入音高检测获得的高低音高形式的参考数据来完成的。吉他敲击的启动检测被用作发出合成沙隆音调的初始触发。该测试是通过使用互相关方法寻找原始沙隆和合成沙隆的声音数据之间的相似性来进行的。测试结果的相似准确率为91.6%。在用生成输出测试吉他弹拨信号的结果上,每次弹拨的平均延迟时间为0.152秒。从获得的结果来看,该系统被归类为足够快速和准确,可以在日常生活中实施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementasi Sintesis Suara Saron Menggunakan Petikan Senar Gitar Dengan Metode Pitch Shifting
 Gamelan is traditional Indonesian musical instruments that is often used in traditional events and parties.The community's need for the gamelan has actually increased, but unfortunately the price of gamelan is very expensive and the gamelan itself is difficult to move from one place to another place. Besides that, the limited tones that can be played by gamelan reduce the level of public interest in playing this instrument. Current technological developments make it possible to perform voice synthesis with several methods. One method that can be used is pitch shifting.This study aims to generate a synthetic saron sound based on plucking a guitar string. Analysis of the saron sound signal in the frequency domain is carried out to obtain the semitone values needed in the synthesis process. Synthetic saron signal generation is done by calling synthetic saron sounds that are stored in soundfont form, with reference data in the form of high and low pitch obtained from the guitar input pitch detection. Onset detection of guitar strokes is used as the initial trigger for calling out synthetic saron tones. The test was carried out by looking for similarities between the sound data of the original saron and synthetic saron using the cross-correlation method. The test results obtained a similarity accuracy rate of 91.6%. On the results of testing the guitar strum signal with the generation output, the average delay time for each strum is 0.152 seconds. From the results obtained, the system is classified as fast and accurate enough to be implemented in everyday life.
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