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 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.

Various systems and methods are disclosed to allow users to conveniently control characteristics of sounds generated by musical instruments. Exemplary systems include a control unit in communication with any number of audio processing devices (APDs). The control unit may be operable to transmit control signals to each of the APDs, wherein the control signals include settings information relating to one or more APD processing parameter values. The control unit may be further operable to receive an audio signal generated by an instrument and transmit the same to the APDs. Accordingly, upon receiving the control signal and the audio signal from the control unit, the APDs may update their processing parameters based on relevant settings information contained in the control signal and process the audio signal into a processed audio signal, based on the updated processing parameters.

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.

A sonification system and method for providing continuous monitoring of complex data metrics, such as that from computer system activity, by taking data from multiple streams and reducing each stream of data into an easily understood audio signal that is easily distinguishable from other audio signals generated from other data streams. The sonification system and method operates to map multi-dimensional data graphs to audio and consists largely of silence, separated by terse and informative audio signals which each provide information related to intensity measurements and quantity measurements during a predetermined time interval.

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.

Various systems and methods are disclosed to allow users to conveniently control characteristics of sounds generated by musical instruments. Exemplary systems include a control unit in communication with any number of audio processing devices (APDs). The control unit may be operable to transmit control signals to each of the APDs, wherein the control signals include settings information relating to one or more APD processing parameter values. The control unit may be further operable to receive an audio signal generated by an instrument and transmit the same to the APDs. Accordingly, upon receiving the control signal and the audio signal from the control unit, the APDs may update their processing parameters based on relevant settings information contained in the control signal and process the audio signal into a processed audio signal, based on the updated processing parameters.

An audio information processing method and apparatus are provided. The method includes decoding a first audio file to acquire a first audio subfile corresponding to a first sound channel and a second audio subfile corresponding to a second sound channel; extracting first audio data from the first audio subfile; extracting second audio data from the second audio subfile; acquiring a first audio energy value of the first audio data; acquiring a second audio energy value of the second audio data; and determining an attribute of at least one of the first sound channel and the second sound channel based on the first audio energy value and the second audio energy value.

An audio information processing method and apparatus are provided. The method includes decoding a first audio file to acquire a first audio subfile corresponding to a first sound channel and a second audio subfile corresponding to a second sound channel; extracting first audio data from the first audio subfile; extracting second audio data from the second audio subfile; acquiring a first audio energy value of the first audio data; acquiring a second audio energy value of the second audio data; and determining an attribute of at least one of the first sound channel and the second sound channel based on the first audio energy value and the second audio energy value.