Disclosed is a learning model generation method executed by a computer, including: striking a percussion instrument with a striking member to emit a musical sound; and conducting machine learning upon receiving an input of the musical sound emitted from the percussion instrument, and generating, based on the machine learning, a learning model for outputting numerical values for setting musical performance parameters for an automatic musical performance of the percussion instrument that is struck when the striking member is driven.

Disclosed is a learning model generation method executed by a computer, including: striking a percussion instrument with a striking member to emit a musical sound; and conducting machine learning upon receiving an input of the musical sound emitted from the percussion instrument, and generating, based on the machine learning, a learning model for outputting numerical values for setting musical performance parameters for an automatic musical performance of the percussion instrument that is struck when the striking member is driven.

A reproduction system includes an output apparatus that outputs multitrack data including a plurality of track-by-track audio data of sounds of (i) musical instruments, (ii) singing voices, or both (i) and (ii), the plurality of track-by-track audio data including audio data of at least an acoustic instrument, a vibrator that vibrates the acoustic instrument in accordance with the audio data of the acoustic instrument included in the plurality of track-by-track audio data included in the multitrack data, and a speaker that outputs the sounds of (i) the musical instruments, (ii) the singing voices, or both (i) and (ii) in accordance with the plurality of track-by-track audio data.

A reproduction system includes an output apparatus that outputs multitrack data including a plurality of track-by-track audio data of sounds of (i) musical instruments, (ii) singing voices, or both (i) and (ii), the plurality of track-by-track audio data including audio data of at least an acoustic instrument, a vibrator that vibrates the acoustic instrument in accordance with the audio data of the acoustic instrument included in the plurality of track-by-track audio data included in the multitrack data, and a speaker that outputs the sounds of (i) the musical instruments, (ii) the singing voices, or both (i) and (ii) in accordance with the plurality of track-by-track audio data.

A percussion instrument motion reproduction device includes a percussion instrument. The percussion instrument includes a vibration portion. The percussion instrument motion reproduction device includes a first driving portion. The first driving portion of the percussion instrument motion reproduction device is configured to visually displace the vibration portion in response to an electrical signal.

A system and method for automatic drumming. A MIDI decoder (1) receives MIDI serial data in real-time, decodes said MIDI serial data to obtain playing instructions, and signals at least one actuator (2) to strike at least one drum according to said decoded playing instructions. User inputs for selecting the MIDI channel and assigning MIDI notes to drums may be provided. The intensity of percussion may be controlled by the MIDI velocity and may be overridden by the user at the MIDI decoder. The at least one actuator may employ a solenoid and comprises features to mitigate latency between the MIDI serial data received and the drum hit. The at least one actuator may comprise a clamping or securement means enabling fast and convenient repositioning thereof. The at least one actuator may comprise means for substitution of a percussion implement, such as a drumstick, brush, or mallet.

A system and method for automatic drumming. A MIDI decoder (1) receives MIDI serial data in real-time, decodes said MIDI serial data to obtain playing instructions, and signals at least one actuator (2) to strike at least one drum according to said decoded playing instructions. User inputs for selecting the MIDI channel and assigning MIDI notes to drums may be provided. The intensity of percussion may be controlled by the MIDI velocity and may be overridden by the user at the MIDI decoder. The at least one actuator may employ a solenoid and comprises features to mitigate latency between the MIDI serial data received and the drum hit. The at least one actuator may comprise a clamping or securement means enabling fast and convenient repositioning thereof. The at least one actuator may comprise means for substitution of a percussion implement, such as a drumstick, brush, or mallet.

A reproduction system includes an output apparatus that outputs multitrack data including a plurality of track-by-track audio data of sounds of (i) musical instruments, (ii) singing voices, or both (i) and (ii), the plurality of track-by-track audio data including audio data of at least an acoustic instrument, a vibrator that vibrates the acoustic instrument in accordance with the audio data of the acoustic instrument included in the plurality of track-by-track audio data included in the multitrack data, and a speaker that outputs the sounds of (i) the musical instruments, (ii) the singing voices, or both (i) and (ii) in accordance with the plurality of track-by-track audio data.

A reproduction system includes an output apparatus that outputs multitrack data including a plurality of track-by-track audio data of sounds of (i) musical instruments, (ii) singing voices, or both (i) and (ii), the plurality of track-by-track audio data including audio data of at least an acoustic instrument, a vibrator that vibrates the acoustic instrument in accordance with the audio data of the acoustic instrument included in the plurality of track-by-track audio data included in the multitrack data, and a speaker that outputs the sounds of (i) the musical instruments, (ii) the singing voices, or both (i) and (ii) in accordance with the plurality of track-by-track audio data.

Disclosed is a learning model generation method executed by a computer, including: striking a percussion instrument with a striking member to emit a musical sound; and conducting machine learning upon receiving an input of the musical sound emitted from the percussion instrument, and generating, based on the machine learning, a learning model for outputting numerical values for setting musical performance parameters for an automatic musical performance of the percussion instrument that is struck when the striking member is driven.