Examples described herein may perform various operations based on mood congruency. An example method involves accessing, by a processor, from a database, a score that represents a degree of congruency between a first mood vector that describes first media data and a second mood vector that describes second media data, wherein the score is generated based on (i) a first value that the first mood vector associates with a first mood, (ii) a second value that the second mood vector associates with a second mood, and (iii) a degree of congruency between the first and second moods, based on the score, comparing, by the processor, a first characteristic of the first media data, other than the first mood, with a second characteristic of the second media data, other than the second mood, and based at least in part on an output of the comparing, providing an indicator to a module.

The present application provides techniques for displaying music score segments in target music videos. The techniques comprise determining a digital music score corresponding to a piece of music comprised in a target music video; determining a segment of the digital music score corresponding to a current playing progress of the target music video based at least in part on a playing progress of the target music video; generating an image of a music score segment corresponding to the segment of the digital music score based on a predetermined condition; and presenting the image on a corresponding interface of playing the target music video.

Techniques are disclosed relating to automatically generating new music content based on image representations of audio files. A music generation system includes a music generation subsystem and a music classification subsystem. The music generation subsystem may generate output music content according to music parameters that define policy for generating music. The classification subsystem may be used to classify whether music is generated by the music generation subsystem or is professionally produced music content. The music generation subsystem may implement an algorithm that is reinforced by prediction output from the music classification subsystem. Reinforcement may include tuning the music parameters to generate more human-like music content.

According to an embodiment, there is provided a system and method for automatically generating a complete music work from a partially completed work provided by a user. One approach uses an artificial intelligence (AI) engine that is trained by creating incomplete works from a database of complete works and then instructing the AI to complete the incomplete works. A comparison is made between the completed works and the originals to determine the effectiveness of the training process. After the AI is trained, it is applied to the user's incomplete work to produce a final music item.

An adaptive music playback system is disclosed. The system includes a composition system that receives information corresponding to user activity levels. The composition system modifies the composition of a song in response to changes in user activity. The modifications are made according to a set of composition rules to facilitate smooth musical transitions.

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.

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 adjusting a virtual environment using recommendations, including: retrieving character information from a character database, where the character information is associated with a character associated with the virtual environment, and the character information includes character appearance information, character position information, and character action information; retrieving profile information from a profile database, where the profile information indicates one or more profile characteristics and at least one profile characteristic is related to music; comparing at least part of the character information with one or more of the profile characteristics to determine a comparison result; generating adjustment information based on the comparison result; sending the adjustment information to a client system through a network; receiving an adjustment reply from the client system through the network; and adjusting information for the virtual environment based on the adjustment reply.

Managing access to digital content in a virtual environment using virtual content rights, including: providing a virtual content rights database comprising data associating a user of the virtual environment with the virtual content rights acquired with respect to the digital content; receiving a request from a device of the user for assignment of the virtual content rights of the digital content, wherein the user uses the device to interface with the processor; updating the virtual content rights database to indicate the assignment of the virtual content rights to the user; receiving data from the device of the user holding the virtual content rights to digital content including songs to create a virtual mix tape having at least one of the songs; and updating the virtual content rights database to indicate sharing of the virtual mix tape by the user within the virtual environment.

A media-content augmentation system includes a processing system that receives input data 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 at least one reference media file, and then splices or fades together selected parts of the media file, thus generating as an output, a media product in which transitions between its contextual themes are aligned with selected temporal events in the input data. The temporarily-varying events take the form of a beginning and an end in the case of a sustained feature, or a specific point in time for a hit point. A method aligns sections in digital media files with temporally-varying events data to compose a media product. The system augments a sensory experience of a user by dynamically changing and then playing selected media files within the context of the categorized themes input to the processing system.