Provided is an automatic music playing control device that automatically plays chords to achieve a good music playing. The automatic music playing control device has at least one processor, wherein the at least one processor probabilistically selects any one of a plurality of timing types that defines the number of sound emissions, probabilistically selects any one of a plurality of note timing tables that defines sound emission timings, corresponding to the selected timing type, and instructs a sound source to emit a chord at a sound emission timing based on the selected note timing table.

A method of generating music contents from input music contents that includes development of models of music composition generation on the basis of business rules and composition rules. In parallel, sounds are prepared, which may be saved in the sound repository. Then, models in the form of source code are sent to a melody generator. Firstly, the generator is set with specific parameters using a controller conforming to MIDI standards and supplemented with composition characteristics read from the user preference database. Next, the contents are sent to automatic generation based on artificial intelligence algorithms and the digital score of the composition with the desired characteristics is generated. Sound tracks of individual instruments are rendered and the rendered tracks are mixed into the final music record. Next, the composition and its record are verified by the critic module using algorithms based on neural networks.

An apparatus for generating a reproducible audio information sequence includes a receiver adapted to receive and decode a signal in which at least one sequence of symbols is encoded to which an audio information sequence is to correspond, memory storing a plurality of reproducible audio elements, a processor configured for associating one of the reproducible audio elements with at least one first symbol included in the sequence of symbols on the basis of the first symbol and of at least one second symbol that, in the sequence of symbols, precedes or follows the first symbol, and a sound generator for outputting audio sequences, configured for cyclically reproducing said reproducible audio information sequence.

Techniques are disclosed relating to automatically generate new music content. In some embodiments, a computing system receivers user input specifying a user-defined music control element. The computing system may train a machine learning model to change both composition and performance parameters based on user adjustments to the user-defined music control element. In embodiments in which composition and performance subsystems are on different devices, one device may transmit configuration information to another device, where the configuration information specifies how to adjust parameters based on user input to the user-defined music control element. Disclosed techniques may facilitate centralized learning for human-like music production while allowing individualized customization for individual users. Further, disclosed techniques may allow artists to define their own abstract music controls and make those controls available to end-users.

An approach is provided in which an information handling system configures a reinforcement learning model based inspiration selections received from a user. The information handling system performs training iterations using the configured reinforcement learning model, which generates multiple actions and multiple rewards corresponding to multiple actions. The information handling system determines that the multiple rewards reach an empirical threshold and, in turn, generates a musical composition based on the multiple actions.

A computer implemented method is provided for generating a prediction of a next musical note by a computer having at least a processor and a memory. A computer processor system is also provided for generating a prediction of a next musical note. The method includes storing sequential musical notes in the memory. The method further includes generating, by the processor, the prediction of the next musical note based upon a music model and the sequential musical notes stored in the memory. The method also includes updating, by the processor, the music model based upon the prediction of the next musical note and an actual one of the next musical note. The method additionally includes resetting, by the processor, the memory at fixed time intervals.

An automated music composition and generation system having an automated music composition and generation engine for processing musical experience descriptors and space parameters selected by the system user. The engine includes: a user taste generation subsystem for automatically determining the musical tastes and preferences of each system user based on user feedback and autonomous piece analysis, and maintaining a system user profile reflecting musical tastes and preferences of each system user; and a population taste aggregation subsystem for aggregating the musical tastes and preferences of the population of system users, and modifying the musical experience descriptors and/or time and/or space parameters provided to the automated music composition and generation engine, so that the digital pieces of composed music better reflect the musical tastes and preferences of the population of system users and meet future system user requests for automated music compositions.

An electronic musical instrument includes a progression speed changing unit that changes a progression of transport using a predetermined formula such that a total time required for the transport to pass through a specific step section of musical piece data is not changed; a parameter setting unit that sets a parameter for the predetermined formula; and a musical phrase generator that generates a musical phrase by assigning the parameter set by the parameter setting unit to the predetermined formula based on the progression of the transport changed by the progression speed changing unit.

An information processing apparatus according to the present disclosure includes a generation unit that generates a model regarding generation of content by using data provided by a user subject of a service regarding creation of the content, the user subject having one authority level among a plurality of authority levels of the service, and a determination unit that determines a usage mode of the model generated by the generation unit according to the one authority level of the user subject.

A non-transitory computer-readable storage medium stored with an automatic music arrangement program, and an automatic music arrangement device are provided. An outer voice note having a highest pitch among notes of which sound production start times are approximately the same in a melody part acquired from musical piece data is identified. A melody part acquired by deleting inner voice notes of which sound production starts within a sound production period of the outer voice note and of which pitches are low from the melody part is generated. Candidate accompaniment parts in which root notes of chords of chord data of the musical piece data are arranged to be produced at sound production timings thereof for each pitch range acquired by shifting a range of pitches corresponding to one octave by one semitone at each time are generated, and an accompaniment part is selected among them.