An electronic musical instrument includes: a memory that stores lyric data including lyrics for a plurality of timings, pitch data including pitches for said plurality of timings, and a trained model that has been trained and learned singing voice features of a singer; and at least one processor, wherein at each of said plurality of timings, the at least one processor: if the operation unit is not operated, obtains, from the trained model, a singing voice feature associated with a lyric indicated by the lyric data and a pitch indicated by the pitch data; if the operation unit is operated, obtains, from the trained model, a singing voice feature associated with the lyric indicated by the lyric data and a pitch indicated by the operation of the operation unit; and synthesizes and outputs singing voice data based on the obtained singing voice feature of the singer.

An accessory for modifying sound output of a musical instrument. The body of the instrument has a soundboard. The accessory includes a sound sensor, an actuator, a fastener, and a controller. The sound sensor engages the body and senses vibration of the body representing the sound output of the musical instrument. The actuator engages the soundboard and deforms the soundboard of the musical instrument so as to modify the sound output of the musical instrument. The sound sensor is preferably arranged distally to the actuator. The fastener engages the accessory to the musical instrument, to locate the actuator against the soundboard of the musical instrument. The controller is connected to the actuator and the sound sensor for receiving and analysing the sound output sensed by the sound sensor, and controlling the actuator in dependence on the sound output sensed by the sound sensor.

An electronic musical instrument includes: a memory that stores a trained acoustic model obtained by performing machine learning on training musical score data and training singing voice data of a singer; and at least one processor, wherein the at least one processor: in accordance with a user operation on an operation element in a plurality of operation elements, inputs prescribed lyric data and pitch data corresponding to the user operation of the operation element to the trained acoustic model so as to cause the trained acoustic model to output the acoustic feature data in response to the inputted prescribed lyric data and the inputted pitch data, and digitally synthesizes and outputs inferred singing voice data that infers a singing voice of the singer on the basis of the acoustic feature data output by the trained acoustic model.

An electronic musical instrument includes: a memory that stores a trained acoustic model obtained by performing machine learning on training musical score data and training singing voice data of a singer; and at least one processor, wherein the at least one processor: in accordance with a user operation on an operation element in a plurality of operation elements, inputs prescribed lyric data and pitch data corresponding to the user operation of the operation element to the trained acoustic model, and digitally synthesizes and outputs inferred singing voice data that infers a singing voice of the singer on the basis of at least a portion of acoustic feature data output by the trained acoustic model, and on the basis of instrument sound waveform data that are synthesized in accordance with the pitch data corresponding to the user operation of the operation element.

A tremolo and tuning apparatus for a stringed musical instrument. The stringed musical instrument includes a body and a neck, a plurality of strings extending from the body to the neck, a nut for supporting the strings on the neck forming a first critical point for each string, a bridge element for supporting the strings on the body forming a second critical point for each string. The apparatus includes a tremolo and tuning apparatus having a one-piece saddle configured to hold unmodified strings which include the ball end uncut. The tremolo and tuning apparatus also includes a plurality of tuner rods disposed atop each string and separate from the saddle. These tuner rods are configured to fine tune each string by a user pressing downward on each tuner rod as needed to tune each string of the stringed musical instrument rather than pulling and releasing tension in each string.

A controller, method, system, and computer-readable medium, for producing control signals. The controller comprises a pressure sensor, a hinged input mechanism configured to receive input forces and direct them towards the sensor, and a processor. The processor is configured to receive a signal from the pressure sensor indicating that the hinged input mechanism is being depressed or released and, based on the received signal, to determine, during a time interval, a rate of change of pressure detected at the sensor. The processor also generates a control signal associated with the hinged input mechanism, wherein the control signal comprises a velocity characteristic representing a speed at which the hinged input mechanism is depressed or released, and the velocity characteristic is based at least partly on the determined rate of change of pressure. In one example embodiment, the control signal is an audio control.

An electronic musical instrument includes: a memory that stores a machine-learning trained acoustic model mimicking voice of a singer and at least one processor. When a vocoder mode is on, prescribed lyric data and pitch data corresponding to a user operation of an operation element of the musical instrument are inputted to the trained acoustic model, and inferred singing voice data that infers a singing voice of the singer is synthesized on the basis of acoustic feature data output by the trained acoustic model and on the basis of instrument sound waveform data that are synthesized in accordance with the pitch data corresponding to the user operation of the operation element. When the vocoder mode is off, the inferred singing voice data is synthesized based on the acoustic feature data without using the sound waveform data.

An electronic musical instrument includes: a memory that stores a trained acoustic model obtained by performing machine learning on training musical score data and training singing voice data of a singer; and at least one processor, wherein the at least one processor: in accordance with a user operation on an operation element in a plurality of operation elements, inputs prescribed lyric data and pitch data corresponding to the user operation of the operation element to the trained acoustic model so as to cause the trained acoustic model to output the acoustic feature data in response to the inputted prescribed lyric data and the inputted pitch data, and digitally synthesizes and outputs inferred singing voice data that infers a singing voice of the singer on the basis of the acoustic feature data output by the trained acoustic model.

An electronic musical instrument includes: a memory that stores a machine-learning trained acoustic model mimicking voice of a singer and at least one processor. When a vocoder mode is on, prescribed lyric data and pitch data corresponding to a user operation of an operation element of the musical instrument are inputted to the trained acoustic model, and inferred singing voice data that infers a singing voice of the singer is synthesized on the basis of acoustic feature data output by the trained acoustic model and on the basis of instrument sound waveform data that are synthesized in accordance with the pitch data corresponding to the user operation of the operation element. When the vocoder mode is off, the inferred singing voice data is synthesized based on the acoustic feature data without using the sound waveform data.

An electronic musical instrument includes: a memory that stores a trained acoustic model obtained by performing machine learning on training musical score data and training singing voice data of a singer; and at least one processor, wherein the at least one processor: in accordance with a user operation on an operation element in a plurality of operation elements, inputs prescribed lyric data and pitch data corresponding to the user operation of the operation element to the trained acoustic model, and digitally synthesizes and outputs inferred singing voice data that infers a singing voice of the singer on the basis of at least a portion of acoustic feature data output by the trained acoustic model, and on the basis of instrument sound waveform data that are synthesized in accordance with the pitch data corresponding to the user operation of the operation element.