A processor-based method of producing a generative musical composition is disclosed herein. The method includes the step of receiving a briefing narrative which describes a musical journey by referencing a plurality of emotional descriptions related to a plurality of musical sections. The generative musical composition is assembled with regard to the briefing narrative through the selection and concatenation of Form Atoms with tags that align with the emotional descriptions related to the musical sections. The Form Atoms, which have compositional nature aligned with the emotional descriptions and self-contained constructional properties representative of the historical corpus of music, are then selected and substituted into the generative composition. The method further involves the step of generating the musical composition by mapping musical transition between selectively chosen Form Atoms to reflect pre-established transitions between Form Atoms and groups Form Atoms that have been identified to have similar tags but different constructional properties.

The disclosure provides a terminal, a terminal communication method, and a communication system. The terminal is connected to a server and connected to an electronic device via the server and includes a correspondence data information storage means, a data association information receiving means, a comparison means, and a display means. The correspondence data information storage means stores correspondence data information of the electronic device. The data association information receiving means receives, from the server, data association information associated with data used for reproduction of sounds or images in the electronic device. The comparison means compares the data association information with the correspondence data information. The display means displays the data association information included in the correspondence data information based on a comparison result obtained by the comparison means.

A method and a system for generating music for an electronic device are provided. The system is configured to generate a first portion of generative music by combining a plurality of audio stems based on a determined first current state vector; measure, with the biosensor, the EEG data while the first portion of generative music is played by the speakers to the user; in response to determining that the current state should be modified to achieve a desired goal state of the user, determine a second set of music parameters for achieving the desired level of focus of the user; generate by the processor and play at the speaker a second portion of generative music characterized by the second set of music parameters to achieve the desired goal state of the user.

The disclosure provides a server, an electronic device, a server communication method, a device communication method, and a communication system. In loading of a communication system, in the case where an identifier of a timbre data and an instruction for loading the timbre data are transmitted from a mobile terminal to a server, the server acquires the timbre data corresponding to the identifier of the timbre data from a timbre DB, and transmits the timbre data together with the received instruction to a communication device (electronic musical instrument). In the electronic musical instrument, the received timbre data is stored to a work memory in response to the instruction received from the server.

The teachings described herein are generally directed to a system, method, and apparatus for separating and mixing tracks within music. The system can have a video that is synchronized with the variations in the musical tempo through a variable timing reference track designed and provided for a user of the preselected performance that was prerecorded, wherein the designing of the variable timing reference track includes creating a tempo map having variable tempos, rhythms, and beats using notes from the preselected performance.

The present disclosure provides a method and a system for realizing intelligent matching and adding of rhythmic tracks. In one example, a method is provided, including: pre-storing a plurality of music elements; generating a rhythmic track library according to the plurality of music elements, the rhythmic track library including a plurality of rhythmic tracks based on the plurality of music elements; detecting a BPM of original music, and calculating a time interval between every two beats based on the detected BPM of the original music; selecting one or more rhythmic tracks from the rhythmic track library, and assigning a time parameter to the one or more rhythmic tracks based on the time interval so as to match the rhythm of the original music; and adding the one or more rhythmic tracks assigned with the time parameter into the original music so as to combine with the original music and play.

A generative composition system reduces existing musical artefacts to constituent elements termed “Form Atoms”. These Form Atoms may each be of varying length and have musical properties and associations that link together through Markov chains. To provide myriad new composition, a set of heuristics ensures that musical textures between concatenated musical sections follow a supplied and defined briefing narrative for the new composition whilst contiguous concatenated Form Atoms are also automatically selected to see that similarities in respective and identified attributes of musical textures for those musical sections are maintained to support maintenance of musical form. Independent aspects of the disclosure further ensure that, within the composition work, such as a media product or a real-time audio stream, chord spacing determination and control are practiced to maintain musical sense in the new composition. Further, a structuring of primitive heuristics operates to maintain pitch and permit key transformation. The system and its functionality provides signal analysis and music generation through allowing emotional connotations to be specified and reproduced from cross-referenced Form-Atoms.

Systems, devices, and methods for encoding the harmonic structure of a musical composition in a digital data structure are described. Tonal and rhythmic commonalities are identified across the musical bars that make up a musical composition. Individual bars of the musical composition are each analyzed to characterize their respective harmonic fingerprints in various forms, and the respective harmonic fingerprints are compared to sort the musical bars into harmonic equivalence categories. Isomorphic mappings between hierarchical data structures that encode the musical composition based on musicality and harmony, respectively, are also described.

The systems, devices, and methods for encoding the harmonic structure of a musical composition in a digital data structure have broad applicability in computer-based composition and variation of music.

Methods, systems and computer program products are provided for testing a lead sheet for plagiarism. A test lead sheet receiving having a plurality of passages is received at receiving a plagiarism detector. A set of annotations describing a level of plagiarism of a plurality of elements (e.g., chord sequence, subsequences, melodic fragments (i.e., notes), rhythm, harmony, etc.) of the test lead sheet in relation to the preexisting lead sheets are generated and output via an output device.

According to an embodiment, there is provided a system and method for automatically generating a complete music work from a partially completed work provided by a user. One approach uses an artificial intelligence (AI) engine that is trained by creating incomplete works from a database of complete works and then instructing the AI to complete the incomplete works. A comparison is made between the completed works and the originals to determine the effectiveness of the training process. After the AI is trained, it is applied to the user's incomplete work to produce a final music item.