A system and method for synchronizing an audio or MIDI file with a video file are provided. The method includes receiving a first audio or MIDI file, receiving a video file, and operating an audio synchronization module to perform steps of synchronizing the first audio or MIDI file with the video file, marking an event in the video file at a point on a timeline, detecting a first musical key for the event, retrieving a musical stinger or swell from a library, in which the musical stinger or swell is a second audio or MIDI file and is tagged with a second musical key, and the second musical key is relevant to the first musical key, and placing the musical stinger or swell at the point of the timeline marked for the event.

Techniques are provided for generating an output file. One technique involves the steps of generating audio or MIDI content blocks from one or more musical performances; receiving an input file having audio or MIDI music content; generating a harmonic chord map for the input file; using the harmonic chord map to automatically select a subset of the audio or MIDI content blocks, and generating the output file by combining the selected subset of content blocks and the input file. This technique may enable the creation of unique and new musical accompaniments by re-purposing audio or MIDI content from back catalogs and/or out-takes of musical works. The new arrangement may be provided in multiple music styles, genres, or moods and may contain performances from multiple musical instruments, which may be pre-recorded from live instrument performances and/or of MIDI generated musical content.

An electronic device and a method for controlling the electronic device, the method including receiving an input of a command to reproduce music contents, determining audio characteristics information on the music contents and situation information on an environment where the music contents are being reproduced; and displaying a visualization effect of visualizing the music contents using the audio characteristics information and the situation information, and reproducing the music contents.

A reproduction control method realized by a computer includes analyzing an actual performance of an actual performer, controlling a reproduction of a performance sound of a musical piece represented by music data in accordance with a result of the analyzing of the actual performance, and outputting a message relating to the actual performance in accordance with the result of the analyzing of the actual performance.

The present invention relates to a method and system for analysing audio (eg. music) tracks. A predictive model of the neuro-physiological functioning and response to sounds by one or more of the human lower cortical, limbic and subcortical regions in the brain is described. Sounds are analysed so that appropriate sounds can be selected and played to a listener in order to stimulate and/or manipulate neuro-physiological arousal in that listener. The method and system are particularly applicable to applications harnessing a biofeedback resource.

A method for electronic music generation comprising electronically applying one or more functions that change one or more compositional elements of a musical input in a first tonality or other musical representation to generate a musical output in a second tonality or other musical representation and recording data corresponding to the musical output in a recording medium or rendering such musical Transformations to a reproductive medium such as an amplifier and speakers or headphones.

This application discloses a method for making music recommendations. The method for making music recommendations is performed by a server device. The method includes obtaining a material for which background music is to be added; determining at least one visual semantic tag of the material, the at least one visual semantic tag describing at least one characteristic of the material; identifying a matched music matching the at least one visual semantic tag from a candidate music library; sorting the matched music according to user assessing information of a user corresponding to the material; screening the matched music based on a sorting result and according to a preset music screening condition; and recommending matched music obtained through the screening as candidate music of the material.

A waveform analysis method utilizes a convolutional neural network (CNN) to differentiate waveform data based on applying one or more pre-trained weights to pre-processed spectrograms sampled uniformly from the waveform data. The CNN outputs, in real-time, the level of confidence that any number of potential custom tags accurately describe the sampled waveform data. These outputs can vary across a single musical track. When these outputs are packaged with the track's metadata, a comprehensive searchable database can be formed which provides quantifiable means of differentiating qualitative features of music.

An artificial intelligence (AI) method includes generating a first musical interaction behavioral model. The first musical interaction behavioral model causes an interactive electronic device to perform a first set of musical operations and a first set of motional operations. The AI method further includes receiving user inputs received in response to the performance of the first set of musical operations and the first set of motional operations and determining a user learning progression level based on the user inputs. In response to determining that the user learning progression level is above a threshold, the AI method includes generating a second musical interaction behavioral model. The second musical interaction behavioral model causes the interactive electronic device to perform a second set of musical operations and a second set of motional operations. The AI method further includes performing the second set of musical operations and the second set of motional operations.

Aspects of the subject disclosure may include, for example, a device that has a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations including: receiving media content from user equipment, wherein the media content comprises a sample of an existing work used to modify an original work; analyzing the media content using machine learning to determine a plurality of composition parameters that characterize aspects of the media content; recording the plurality of composition parameters determined, including an identification of composition parameters in the plurality of composition parameters attributable to the existing work, and an identification of composition parameters attributable to the original work, in a blockchain ledger; searching for the composition parameters in the blockchain ledger for one or more works having similar composition parameters; and reporting any works found during the searching to the user equipment.