  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.

Sound;Audio and Speech Processing