A type estimation model generation system is a system that generates a type estimation model used for type estimation of estimating one of a plurality of types to which a user belongs, the system including: a learning data acquiring unit configured to acquire learning time series information that is information of a time series about a plurality of used musical pieces and learning type information representing types to which users who have used the plurality of musical pieces belong that are learning data used for machine learning; and a model generating unit configured to generate the type estimation model by performing machine learning using information based on the learning time series information as an input for the type estimation model in units of musical pieces in order of the time series and information based on the learning type information as an output of the type estimation model.

A system providing a music service platform includes a music controller device, a client device, and a server. The music controller device receives musical data indicative of a music performance by an individual and generates metadata characterizing the musical data. The client device includes a software application that receives the musical data and the metadata from the music controller device and presents a graphical user interface for display on the client device. The graphical user interface includes information related to the musical data and the metadata. The server receives the musical data and the metadata, generates one or more analytics associated with the musical data, and performs one or more data aggregation techniques on the musical data.

An electronic musical instrument, method for a musical sound generation process and a non-transitory computer readable medium that stores an electronic musical instrument program are provided. The program causes a computer provided with a storage part to execute a musical sound generation process using sound data. The program causes the computer to execute:

acquiring, from the storage part, first sound data and first user identification information indicating a user who has acquired the first sound data from a distribution server; acquiring second user identification information indicating a user who causes the musical sound generation process to be executed using the first sound data; determining whether or not the first user identification information matches the second user identification information; and inhibiting execution of the musical sound generation process using the first sound data in a case when the first user identification information does not match the second user identification information.

Techniques are described herein for tracking and analyzing musical activity (e.g., musical performances) captured by a music controller device. Data indicative of a musical performance by an individual is received. Metadata characterizing the musical data is generated. One or more analytics of the musical data is generated based, at least in part, on the metadata.

An instructional method of an electronic keyboard includes the following steps: obtaining a playing script, wherein the playing script is generated by a recording electronic keyboard; the recording electronic keyboard generates the playing script according to a pressed second key and the time of pressing the second key, and the playing script is used for indicating a corresponding relationship between a to-be-pressed key and the time of pressing the to-be-pressed key; controlling an indicator light on the first key of the instructional electronic keyboard to be turned on/off according to the playing script. In this implementation mode, a user can be prompted for the key by an indicator light on the electronic keyboard, which facilitates the user to learn the electronic keyboard.

Techniques are described herein for generating a music fingerprint representative of a performance style of an individual. One or more characteristics associated with musical data are identified. A score to associated with each of the identified one or more characteristics is determined. The music fingerprint is generated based on the determine score for each of the identified one or more characteristics.

An instructional method of an electronic keyboard includes the following steps: obtaining a playing script, wherein the playing script is generated by a recording electronic keyboard; the recording electronic keyboard generates the playing script according to a pressed second key and the time of pressing the second key, and the playing script is used for indicating a corresponding relationship between a to-be-pressed key and the time of pressing the to-be-pressed key; controlling an indicator light on the first key of the instructional electronic keyboard to be turned on/off according to the playing script. In this implementation mode, a user can be prompted for the key by an indicator light on the electronic keyboard, which facilitates the user to learn the electronic keyboard.

A cloud-based recording studio infrastructure includes a remote recording studio system including a cloud computing module configured to instantiate a virtual machine instance associated with a user and dynamically provision computing resources to the virtual machine instance associated with the user, the virtual machine instance associated with the user being configured as a music production environment, a cloud storage module configured to manage a cloud storage network, store an uploaded file from the user to the cloud storage network, and restrict access to one or more resources stored on the cloud storage network to the virtual machine instance associated with the user, and a connection manager module configured to authenticate the user and manage access to the virtual machine instance associated with the user.

Techniques are described herein for generating a music fingerprint representative of a performance style of an individual. One or more characteristics associated with musical data are identified. A score to associated with each of the identified one or more characteristics is determined. The music fingerprint is generated based on the determine score for each of the identified one or more characteristics.

A system providing a music service platform includes a music controller device, a client device, and a server. The music controller device receives musical data indicative of a music performance by an individual and generates metadata characterizing the musical data. The client device includes a software application that receives the musical data and the metadata from the music controller device and presents a graphical user interface for display on the client device. The graphical user interface includes information related to the musical data and the metadata. The server receives the musical data and the metadata, generates one or more analytics associated with the musical data, and performs one or more data aggregation techniques on the musical data.