A computer-implemented method of digital music composition that creates a digital multi-genre musical composition track by downloading a host digital music track of a first genre and two or more separate donor multi-genre musical tracks, and then selectively modulating the instruments and rhythmic patterns of the donor musical tracks by manipulating the rhythmic patterns. The manipulation includes manipulating at least one of the intensities, frequency, sound, beat, and rhythm of the rhythmic pattern. The manipulated donor musical tracks are then integrated into the host musical track to create a combined digital multi-genre musical composition track, which can be downloaded, saved in a file, and replayed as needed.

Systems and techniques for removing a sound recording from an audio recording (e.g., an audio recording embedded in a media file) are presented. The system can include an identification component, a first subtraction component and a second subtraction component. The identification component identifies a sound recording in a mixed audio recording. The first subtraction component determines a local linear transformation of the sound recording and subtracts the local linear transformation of the sound recording from the mixed audio recording to generate a new mixed audio recording. The second subtraction component compares one or more segments of the sound recording with one or more corresponding segments of the new mixed audio recording and reduces a power level of the new mixed audio recording based at least in part on correlation of the one or more corresponding segments with the one or more segments.

Systems and methods for generating a graphical representation of audio-file playback during playback manipulation are provided. The system may include a processor that performs a method including displaying a waveform during audio-file playback by scrolling the waveform from a right to a left portion of a display. The method includes receiving a command to manipulate the audio-file playback and displaying a first half of the waveform corresponding to the manipulated audio-file playback until a command is received to resume the audio-file playback. The first half of the waveform is a portion of the waveform adjacent to a horizontal or vertical axis. The method includes simultaneously displaying a second half of the waveform and displaying the first half of the waveform corresponding to the manipulated audio-file playback. The second half of the waveform is on an opposite side of the axis from the first half of the waveform.

A method of creating AI-composed music having a style that reflects and/or augments the personal style of a user includes selecting and/or composing one or more seed compositions; applying variation and/or mash-up methods to the seed compositions to create training data; training an AI using the training data; and causing the AI to compose novel musical compositions. The variation methods can include methods described in the inventor's previous patents. A novel method of creating mash-ups is described herein. Variation and mash-up methods can further be applied to the A compositions. The AI compositions, and/or variations and/or mash-ups thereof, can be added to the training data for re-training of the AI. The disclosed mash-up method includes parsing the seed compositions into sequences of elements, which can be of equal length, beat-matching the seed compositions to make corresponding elements of equal beat length, and combining the elements to form a mash-up.

The present invention relates to systems and methods for visual image audio composition. In particular, the present invention provides systems and methods for audio composition from a diversity of visual images and user determined sound database sources.

An electronic device segments a first and second MIDI files into pluralities of source segments and target segments. For each of a plurality of consecutive pairs of first and second target segments, the electronic device identifies a first source segment corresponding to the first target segment of the consecutive pair and identifies a second source segment corresponding to the second target segment of the consecutive pair, where the first and second source segments are identified by determining that the first and second source segments are harmonically conformant to the corresponding first and second target segments, and determining that a transition between the first and second source segments is graphically conformant to a transition between a consecutive pair of source segments. The electronic device generates a third MIDI file using the identified first and second source segments for each of the plurality of consecutive pairs of first and second target segments.

Systems and methods for generating a visual color display of audio-file data are provided. The system includes a processor that performs a method including receiving audio-file data; generating filtered-audio data by processing the audio-file data by frequency-band filters. The frequency band filters have different frequency bands. The method includes generating one or more waveforms corresponding to the filtered-audio data and displaying the waveforms superimposed in unique color relative to one another. The method includes downsampling the waveforms. The method includes processing the waveforms through an envelope detector. The method includes processing the waveforms through an expander and applying a gain factor. The waveforms have transparency levels at sections that are proportional or inversely proportional to amplitudes at the sections.

Methods, systems and computer program products are provided for determining acoustic feature vectors of query and target items in a first vector space, and mapping the acoustic feature vectors to a second vector space having a lower dimension. The distribution of vectors in the second vector space can then be used to identify items from the same songs, and/or items that are complementary. A mapping function is trained using a machine learning algorithm, such that complementary audio items are closer in the second vector space than the first, according to a given distance metric.

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.

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.