Text-to-Speech Synthesis Techniques for MIDI-to-Audio Synthesis

Erica Cooper; Xin Wang; Junichi Yamagishi

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arXiv · 2104.12292

Text-to-Speech Synthesis Techniques for MIDI-to-Audio Synthesis

Erica Cooper·Xin Wang·Junichi Yamagishi

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Abstract

Speech synthesis and music audio generation from symbolic input differ in many aspects but share some similarities. In this study, we investigate how text-to-speech synthesis techniques can be used for piano MIDI-to-audio synthesis tasks. Our investigation includes Tacotron and neural source-filter waveform models as the basic components, with which we build MIDI-to-audio synthesis systems in similar ways to TTS frameworks. We also include reference systems using conventional sound modeling techniques such as sample-based and physical-modeling-based methods. The subjective experimental results demonstrate that the investigated TTS components can be applied to piano MIDI-to-audio synthesis with minor modifications. The results also reveal the performance bottleneck -- while the waveform model can synthesize high quality piano sound given natural acoustic features, the conversion from MIDI to acoustic features is challenging. The full MIDI-to-audio synthesis system is still inferior to the sample-based or physical-modeling-based approaches, but we encourage TTS researchers to test their TTS models for this new task and improve the performance.

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BibTeX RIS

Erica Cooper, Xin Wang, Junichi Yamagishi. 2022-02-24. Text-to-Speech Synthesis Techniques for MIDI-to-Audio Synthesis. https://arxiv.org/abs/2104.12292

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