Deep Neural Networks for Sound Synthesis of Thai Duct F1ute, Khlui

Tantep Sinjankhom, S. Chivapreecha, N. Chitanont, Tomonori Kato
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Abstract

This paper introduces Thai musical instrument sound synthesis with an intelligent technique which is a combination of deep neural networks and conventional signal processing techniques. The instrument focused on in this paper is the Khlui, which is a unique Thai reedless wind instrument. Khlui sound can be synthesized by performing a combination of additive and subtractive syntheses. The synthesis system takes the pitch and loudness of any monophonic input signal. Then, multilayer perceptron and recurrent neural networks are used together in order to generate 3 parameters which are harmonic distribution, filter magnitude response, and the signal envelope. Finally, the harmonic characteristic of the Khlui along with the blowing noises are highly synthesized. The results are natural-sounding and realistic when compared with the recorded Khlui audio. This research will contribute to the more convenient natural synthesis of the Khlui sounds.
基于深度神经网络的泰国管道管声合成[j]
本文介绍了一种将深度神经网络与传统信号处理技术相结合的智能泰式乐器声音合成技术。本文研究的乐器是Khlui,这是一种独特的泰国无簧片管乐器。Khlui音可以通过执行加法和减法合成的组合来合成。合成系统接收任何单音输入信号的音高和响度。然后,将多层感知器与递归神经网络结合使用,生成谐波分布、滤波器幅值响应和信号包络3个参数。最后,对吹笛声的谐波特性进行了高度综合。与录制的Khlui音频相比,结果听起来很自然,很真实。这项研究将有助于更方便地自然合成Khlui音。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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