According to an embodiment, there is provided a system and method for automatic AI controlled loop based song construction. It provides and benefits from a machine learning AI in a audio loop selection engine for the generation of a song structure and for the selection of fitting audio loops from a database of audio loops. In one embodiment, the instant method provides a music generation process that utilizes an AI system that has been trained and validated on a music item database to complete the creation of a music item given an incomplete song that was started but not finished by a user.

Disclosed are a method for controlling a sound quality based on a voice command and an apparatus therefor. According to an exemplary embodiment of the present disclosure, a sound quality control method based on a voice command includes a voice command acquiring step of acquiring a voice command for playing media contents, a voice command analyzing step of recognizing the media contents by analyzing the voice command and generating recognition result information for the media contents, a category determining step of determining a category for the media contents based on the recognition result information, and a sound quality setting control step of determining a play sound quality mode of the media contents based on a determination result of the category.

Methods, apparatus, systems and articles of manufacture are disclosed for dynamic volume adjustment via audio classification. Example apparatus include at least one memory; instructions; and at least one processor to execute the instructions to: analyze, with a neural network, a parameter of an audio signal associated with a first volume level to determine a classification group associated with the audio signal; determine an input volume of the audio signal; determine a classification gain value based on the classification group; determine an intermediate gain value as an intermediate between the input volume and the classification gain value by applying a first weight to the input volume and a second weight to the classification gain value; apply the intermediate gain value to the audio signal, the intermediate gain value to modify the first volume level to a second volume level; and apply a compression value to the audio signal, the compression value to modify the second volume level to a third volume level that satisfies a target volume threshold.

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.

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. Each digital piece of composed and generated music contains a set of musical notes arranged and performed in the digital piece of music. The engine includes: a digital piece creation subsystem and a digital audio sample producing subsystem supported by virtual musical instrument libraries.

Methods, apparatus, systems and articles of manufacture are disclosed for dynamic volume adjustment via audio classification. Example apparatus include at least one memory; instructions; and at least one processor to execute the instructions to: analyze, with a neural network, a parameter of an audio signal associated with a first volume level to determine a classification group associated with the audio signal; determine an input volume of the audio signal; determine a classification gain value based on the classification group; determine an intermediate gain value as an intermediate between the input volume and the classification gain value by applying a first weight to the input volume and a second weight to the classification gain value; apply the intermediate gain value to the audio signal, the intermediate gain value to modify the first volume level to a second volume level; and apply a compression value to the audio signal, the compression value to modify the second volume level to a third volume level that satisfies a target volume threshold.

An automated music composition and generation process within an automated music composition and generation system driven by lyrical musical experience descriptors. The process involves the system user accessing said automated music composition and generation system, employing an automated music composition and generation engine having a system user interface. The system user interface is used to select and provide musical experience descriptors, including lyrics, to the automated music composition and generation engine for processing by said automated music composition and generation engine. The system user initiates the automated music composition and generation engine to compose and generate music based on the musical experience descriptors and lyrics provided.

An automated music composition and generation process within an automated music composition and generation system driven by lyrics. The process involves the system user accessing said automated music composition and generation system, employing an automated music composition and generation engine having a system user interface. The system user interface is used to provide lyrics to the automated music composition and generation engine for processing by the automated music composition and generation engine. The system user initiates the automated music composition and generation engine to compose and generate music based on lyrics the provided as input. The lyrics are analyzed for vowel formants to generate pitch events, which are used to support the automated music composition process.

In some implementations, a user can play a music track from a dynamically generated playlist. The user can provide input indicating that the user likes or dislikes the music track and the playlist can be adjusted based on the user input. In some implementations, information can be presented to the user so that the user can preview changes to the playlist before the changes are made to the playlist. In some implementations, a user can adjust playlist criteria (configuration) by adjusting specific music characteristics. In some implementations, a user can adjust playlist criteria by manipulating a list of representative music tracks. In some implementations, a user can compare the user's playlist to playlists of other users.

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.