A system for generating audio content in dependence upon an input audio track comprising audio corresponding to one or more sound sources, the system comprising an audio input unit operable to input the input audio track to one or more models, each representing one or more of the sound sources, and an audio generation unit operable to generate, using the one or more models, one or more audio tracks each comprising a representation of the audio contribution of the corresponding sound sources of the input audio track, wherein the generated audio tracks comprise one or more variations relative to the corresponding portion of the input audio track.

A processor in an audio extraction apparatus performs a preprocessing operation to determine, for a stereo audio source including first channel audio data including an accompaniment sound and a vocal sound for a first channel and second channel audio data including an accompaniment sound and a vocal sound for a second channel, a difference between the first channel audio data and the second channel audio data to generate center cut audio data, and an audio extraction operation to input the first channel audio data, the second channel audio data and the center cut audio data to a trained machine learning model to extract any one of the accompaniment sound and the vocal sound.

A data generation device includes: an acquisition part configured to acquire measurement data that corresponds to measurement values, obtained in chronological order, corresponding to a behavior of a key or a member coordinating with the key for each of a plurality of keys; and a data generation part configured to generate display data for displaying a screen showing the measurement values corresponding to each of the plurality of keys along a time axis based on the acquired measurement data.

Systems and methods for mapping parts in a digital sheet music file for a harmony. The method may include receiving a selection of a music segment for part mapping, receiving a digital sheet music representation of the selected music segment, and determining a plurality of plausible part mapping for the digital sheet music representation. A part mapping identifies one or more distinct musical parts in the digital sheet music representation, each of said one or more distinct musical parts corresponding to a performer of the harmony. The method may also include analyzing one or more features of the plurality of plausible part mapping to identify a highest probability part mapping based on previously stored information, and outputting the highest probability part mapping.

A chord information extraction device includes an acquirer, a score type determiner, an extraction region determiner and a chord information extractor. The acquirer acquires score image data representing a reference score. The score type determiner determines a score type of the reference score from among a plurality of predetermined score types based on the acquired score image data. The extraction region determiner determines a chord extraction region in the reference score based on extraction region information that defines a relationship between a plurality of score types and a chord extraction region from which chord information is to be extracted. The chord information extractor extracts the chord information from the acquired score image data based on the determined chord extraction region.

A chord information extraction device includes a character group extractor, a determiner and a corrector. The character group extractor extracts a character group corresponding to chord information from score image data representing a music score. The determiner determines whether the character group extracted by the character group extractor follows a predetermined chord notation rule. In a case where the character group extracted by the character group extractor does not follow the chord notation rule, the corrector corrects the extracted character group to follow the chord notation rule.

A method for performing melody detection comprises interpreting the global perceptual effect of all the sounds at once, to determine what is the melody actually perceived by the human ear, and providing a music sheet or a text printout including a time sequence of single notes describing that melody.

A music piece analyzer includes: a beat interval acquiring unit configured to acquire a beat interval in music piece data; a candidate detector configured to detect sounding positions where a change amount for sounding is equal to or more than a predetermined threshold in the music piece data, as candidates for sounding positions of a snare drum; and a sounding position determination unit configured to determine that the candidates for the sounding positions at a two-beat interval acquired by the beat interval acquiring unit in the music piece data are the sounding positions of the snare drum, among the candidates for the sounding positions of the snare drum.

Aspects of the subject disclosure may include, for example, receiving content in the form of musical score sheets or other data that includes instructions to play notes on a particular instrument, guidance that is enabled with respect to the content, obtaining new input such as musical scores or other instructions responsive to determining that the guidance is enabled, and obtaining the guidance with respect to a display of the content, where the obtained guidance is based on the input. The instructions may include the end user take certain action in playing the instrument or physical action in a marching band context. Artificial intelligence may be used to issue new documents, instructions or guidance. A GPS and drone communications system is also disclosed. Other embodiments are disclosed.

A method of generating a musical score file for one or more target musical instruments with a score generation component based on input audio data. The score generation component finds candidate musical notes within the input audio data using a frequency analysis to identify segments that share substantially the same audio frequency, and finds a best match for those candidate musical notes in audio data associated with target musical instruments in a sound database. A generated musical score file can be printed as sheet music or audibly played back over speakers.