An automated music composition and generation system including a system user interface for enabling system users to review and select one or more musical experience descriptors, as well as time and/or space parameters; and an automated music composition and generation engine, operably connected to the system user interface, for receiving, storing and processing musical experience descriptors and time and/or space parameters selected by the system user, so as to automatically compose and generate one or more digital pieces of music in response to the musical experience descriptors and time and/or space parameters selected by the system user. The automated music composition and generation engine includes: a digital piece creation subsystem for creating and delivering the digital piece of music to the system user interface; and a digital audio sample producing subsystem supported by virtual musical instrument libraries.

A method to author music. The method includes presenting, on a display by a computing device, an audio effect menu, receiving, by the computing device, a first user input selecting a first audio effect from the audio effect menu, generating, in response to receiving the first user input, a first modified audio stream based on a particular audio stream and the first audio effect, receiving, by the computing device while receiving the first user input, a second user input selecting a second audio effect from the audio effect menu, generating, in response to receiving the second user input, a second modified audio stream based on the first modified audio stream and the second audio effect, detecting cessation of the first user input, and continuing, in response to detecting the cessation, generating the second modified audio stream based on the first modified audio stream and the second audio effect.

Performance information of one or more accompaniment parts is extracted from original performance information. Arranged accompaniment performance information is created using, in accordance with a predetermined arranging condition, only any one or more of pitch names included in the extracted accompaniment performance information. The predetermined arranging condition comprises instructing that any of chord component notes be thinned out in an identified chord progression, and arranged accompaniment performance information is created by thinning out an accompaniment note of a pitch name corresponding to the chord component note having been instructed to be thinned out. Another predetermined arranging condition comprises setting a ratio between chords and arpeggios in one or more measures, and a combination of chords and arpeggios in the extracted accompaniment part performance information is changed so that a ratio between chords and arpeggios in one or more measures in the extracted accompaniment performance information assumes the set ratio.

An automated music composition and generation system for automatically composing and generating digital pieces of music using an automated music composition and generation engine driven by a set of emotion-type and style-type musical experience descriptors and time and/or space parameters supplied by a system user during an automated music composition and generation process. The system includes a system user interface allowing a system user to input (i) linguistic and/or graphical icon based musical experience descriptors, and (ii) a video, audio-recording, image, slide-show, or event marker, as input through the system user interface.

According to an embodiment, there is provided a system and method for automatic AI-based song construction based on ideas of a user. It provides and benefits from a combination of expert knowledge resident in an expert engine which contains rules for a musically correct song generation and machine learning in an AI-based audio loop selection engine for the selection of fitting audio loops from a database of audio loops. Additionally, in some embodiments there is provided a method of energy-based song construction where the tracks of a multi-track work are balanced depending on the desired output volume level of the final project.

According to an embodiment, there is provided a system and method for automatic AI-based song construction based on ideas of a user. It provides and benefits from a combination of expert knowledge resident in an expert engine which contains rules for a musically correct song generation and machine learning in an AI-based audio loop selection engine for the selection of fitting audio loops from a database of audio loops. Additionally, in some embodiments there is provided a method of energy-based song construction where the tracks of a multi-track work are balanced depending on the desired output volume level of the final project.

An auditory augmentation system includes a database with a multiplicity of audio sections and associated metadata for digital audio files. Each audio section is mapped to a contextual theme, each contextual theme being mapped to an audio section having an entry point and an exit point. The entry and exit points support seamless splice or fade transitions between different audio sections. A processing system couples to the database along with an input; the input is in the form of temporally-varying events data that defines a temporal input. The processing system resolves the temporal input into one or more of a plurality of categorized contextual themes, correlates the categorized contextual themes with metadata associated with selected audio sections relevant to the one or more categorized contextual themes, and splices or fades together selected audio sections, and generates, as an output, a media product in which transitions between audio sections are seamless.

Methods and systems for automatic audio loop generation from an audio track identify suitable portions of the audio track for generating audio loops. One or more embodiments identify portions of the audio track that include a beginning beat and an ending beat that have similar audio features that provide for seamless transitions when generating the audio loops. One or more embodiments generate scores for the portions based on the similarity of the audio features of the corresponding beginning and ending beats. Additionally, one or more embodiments use the generated scores to determine whether each portion is a suitable audio loop candidate. One or more embodiments then generate one or more audio loops using one or more suitable portions of the audio track.

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.

The present disclosure relates to an apparatus, system, and method that allow non-musicians to compose and perform a musical composition. Although some existing electronic devices can provide a virtual environment to compose and play musical sound digitally, manipulating such a virtual environment can be difficult and may require specific software expertise, as well as knowledge of music theory. The present disclosure provides a platform that facilitates the creation of a musical composition without such software expertise or knowledge of music theory. The platform models a musical composition as a simultaneous playback of one or more musical contents. The platform allows players to control or modify one or more of the plurality of musical contents to generate or synthesize a musical composition.