Real-time jamming is automatically assisted for musicians. A real-time audio signal is received of played music that is played by at least one person. Beat is tracked of the played music from the real-time audio signal and accordingly a time of a next beat is predicted. At least one of chords; notes; and drum sounds is recognized from the real-time audio signal and repetitions in the played music are accordingly detected. A next development is predicted in the played music, based on the detected repetitions, including at least one of chords; notes; and drum sounds that will be played next, and respective timing based on the predicted time of the next beat. A real-time output is produced based on the predicted next development in the played music.

A media-content augmentation system includes a database with a multiplicity of media files and associated metadata. Each media file is mapped to at least one contextual theme defined by beginning and end timings. A processing system couples to the database; and an input couples to the processing system. The input is in the form of temporally-varying events data. The processing system resolves the input into one or more categorized contextual themes, correlates the themes with metadata associated with selected media files relevant to the themes, and then splices or fades together selected media files to reflect the events as the input varies with time, thus generating as an output, a media product in which transitions between media are aligned with the temporally-varying events. The database may contain sections of digital media files. A method aligns sections in digital media files with temporally-varying events data to compose a media product.

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.

An information processing method includes generating performance data that represent a performance of a musical piece that reflects a change caused by a factor that alters the performance of the musical piece, by inputting musical score data, which represent a musical score of the musical piece, and variability data, which represent the factor, into a trained model.

A music composition, editing, and playback system and method provides a user interface design based on geometric interpretation of music theory replacing traditional modern music notation with geometric shapes including chords represented by polygons that are colored with colors or hues.

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.

An autonomous music composition and performance system employing an automated music composition and generation engine configured to receive musical signals from a set of a real or synthetic musical instruments being played by a group of human musicians. The system buffers and analyzes musical signals from the set of real or synthetic musical instruments, composes and generates music in real-time that augments the music being played by the band of musicians, and/or records, analyzes and composes music recorded for subsequent playback, review and consideration by the human musicians.

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.

A musical audio composition is generated based on a content library. The library is a collection of sequences and instruments. Sequences are partial musical compositions, while instruments are groups of audio samples. Instruments are made of audio data and musical data describing the events recorded in the audio. The process begins by reading the library. A new chain is created. A succession of sequences are selected to create a series of segments in the chain. The events in the selected sequences determine the selection of instruments. Algorithms determine the final arrangements and exact modulations of source audio to target outputs. The source audio are modulated, mixed and output as a stream of audio data. Finally the selections and events of the finished segment are output as metadata. An unlimited number of segments can be fabricated in series, each building and evolving from the preceding segments in the chain.

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 provided by a system user. The automated music composition and generation engine includes an instrument subsystem supporting a library of virtual instruments, wherein each virtual instrument is capable of performing one or more notes of at least a portion of the composed piece of music, in response to the emotion-type and/or style-type musical experience descriptors; an instrument selector subsystem for automatically selecting one or more of virtual instruments from the library, so that each selected virtual instrument performs one or more notes of at least a portion of the composed piece of music; and a digital piece creation subsystem for creating the digital piece of composed music by assembling the notes produced from the virtual instruments selected from the library.