According to an embodiment, there is provided a system and method for automatic AI-based song construction based on ideas of a user. In some embodiments, an embodiment is provided with a database that contains harmony templates which can be used by the user to augment the playback of a given music work. Various embodiments of the instant invention also benefit from a combination of expert knowledge resident in an expert engine which contains rules for musically correct song generation and machine learning in an AI-based audio loop selection engine for the selection of compatible audio loops from a database of audio loops.

A music generation system is provided comprising a processor and a memory operatively coupled to the processor and storing a rhythm template database comprising a plurality of rhythm templates, and a music generation program stored in the memory and executed by the processor to be configured to receive a user input of lyrics, identify a plurality of syllables in the lyrics, determine a syllable pattern in the identified plurality of syllables, match the syllable pattern to a selected rhythm template of the plurality of rhythm templates, generate a melody based on the selected rhythm template, generate a music file encoding the melody and the lyrics, and output the music file encoding the melody and the lyrics.

In accordance with implementations of the subject matter described herein, there is provided a solution for supporting a machine to automatically generate a song. In this solution, an input from a user is used to determine a creation intention of the user with respect to a song to be generated. Lyrics of the song are generated based on the creation intention. Then, a template for the song is generated based at least in part on the lyrics. The template indicates a melody matching with the lyrics. In this way, it is feasible to automatically create the melody and lyrics which not only conform to the creation intention of the user but also match with each other.

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.

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.

The automatic performance device includes a storage part for storing a plurality of performance patterns, a performance part for playing a performance on the basis of a performance pattern stored in the storage part, an input part for inputting performance information through an input device that receives a performance operation of a user, and a selection part for selecting a performance pattern being a maximum likelihood estimation from the plurality of performance patterns stored in the storage part on the basis of the performance information input to the input part.

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.

In accordance with implementations of the subject matter described herein, there is provided a solution for supporting a machine to automatically generate a song. In this solution, an input from a user is used to determine a creation intention of the user with respect to a song to be generated. Lyrics of the song are generated based on the creation intention. Then, a template for the song is generated based at least in part on the lyrics. The template indicates a melody matching with the lyrics. In this way, it is feasible to automatically create the melody and lyrics which not only conform to the creation intention of the user but also match with each other.

An environment awareness system includes a memory and first and second modules. The memory is configured to store environmental data, one or more music composition templates, and one or more maps, where the environmental data is indicative of at least one of a state, condition, or change in an environment in which the environment awareness system is located. The first module is configured to receive and store the environmental data in the memory. The second module is configured to: based on the one or more music composition templates and the one or more maps, convert the environmental data to a music signal including modifying variables in the one or more music composition templates based on the environmental data; and based on the music signal, play out a musical composition via an audio system to audibly indicate the at least one of the state, condition, or change in the environment.

A request for an audio arrangement having one or more target audio arrangement characteristics is received. One or more target audio attributes are identified based on the one or more target audio arrangement characteristics. First audio data is selected. The first audio data has a first set of audio attributes, which comprises at least some of the identified one or more target audio attributes. Second audio data is selected. The second audio data has a second set of audio attributes, which comprises at least some of the identified one or more target audio attributes. One or more mixed audio arrangements are output and/or data useable to generate the one or more mixed audio arrangements is output. The one or more mixed audio arrangements are generated by at least the selected first and second audio data being mixed using an automated audio mixing procedure.