An audio signal analysis system comprises an electronic controller that is configured to execute a plurality of modules including an acquisition module configured to acquire a first spectrum, which is a time average of a plurality of frequency spectra of an audio signal, a specification module configured to acquire a plurality of reference values corresponding to different pitches that follow a prescribed temperament and configured to specify, by a problem-solving search algorithm, a frequency difference corresponding to a second spectrum which includes a plurality of components each having a frequency difference with respect to each of the plurality of reference values, the second spectrum being similar to the first spectrum with a degree of similarity exceeding a prescribed threshold value, and a correction module configured to correct the frequency difference so as to reduce systematic error included in the frequency difference specified by the specification module.

The Instant Music Composing Music Producing Software Application System will optimize the music writing, composing, producing and arranging experience by providing a convenient and thorough Instant Music Composing/Music Producing Software. This Automated Digital Producer and Composer is useful in the Music Production and Songwriting and Composing areas within the Music Industry; comparable to renown Digital Music Production Software such as ‘Fruity Loops”, Logic, Cubasic, and Protools.

The Instant Music Composing Music Producing Software Application provides a complete and convenient instant music maker, whereas the computations are unlimited combinations and sequences of its pre-stored database of loops, samples, music instrument sound, etc., that ultimately can create unlimited new songs.

Disclosed herein is a method for facilitating creating of music in real time by multiple users, in accordance with some embodiments. Accordingly, the method comprises receiving first music segment selections from a first user device, receiving second music segment selections from a second user device, transmitting the first music segment selections to the second user device, and transmitting the second music segment selections to the first user device. Further, each of the first user device and the second user device is configured for retrieving the first music segments, retrieving the second music segments, determining a universal time, synchronizing the second music segments with the first music segments to a common musical beat based on the universal time, mixing the second music segments with the first music segments based on the synchronizing, and generating a mixed music comprising the first music segments and the second music segments based on the mixing.

Methods, systems, and apparatus, including medium-encoded computer program products, for receiving outputs from a plurality of models that are each informed by real-time data provided by one or more sensors that are present in an aquaculture environment. An input is generated for an algorithmic music composer for algorithmically composing music that reflects multiple current conditions within the aquaculture environment, based at least on the received outputs from the plurality of models. The input is provided to the algorithmic music composer to algorithmically compose the music that reflects the multiple current conditions within the aquaculture environment.

A sound generation method that is realized by a computer includes receiving a representative value of a musical feature amount for each of a plurality of sections of a musical note, and using a trained model to process a first feature amount sequence in accordance with the representative value for each section, thereby generating a sound data sequence corresponding to a second feature amount sequence in which the musical feature amount changes continuously.

Musical catalog amplification services that leverage or deploy a computer-based musical composition system are described. The computer-based musical composition system employs algorithms and, optionally, artificial intelligence to generate new music based on analyses of existing music. The new music may be wholly distinctive from, or may include musical variations of, the existing music. Rights in the new music generated by the computer-based musical composition system are granted to the rights holder(s) of the existing music. In this way, the musical catalog(s) of the rights holder(s) is/are amplified to include additional music assets. The computer-based musical composition system may be tuned so that the new music sounds more like, or less like, the existing music of the rights holder(s). Revenues generated from the new music are shared between the musical catalog amplification service provider and the rights holder(s).

Computer-based systems, devices, and methods for assigning mood labels to musical compositions are described. A mood classifier is trained based on mood-labeled musically-coherent segments of musical compositions and subsequently applied to automatically assign mood labels to musically-coherent segments of musical compositions. In both cases, the musically-coherent segments are generated using automated segmentation algorithms.

Computer-based systems, devices, and methods for generating variations of musical compositions are described. Musical compositions stored in digital media include one or more music data object(s) that encode notes. A first set of notes is characterized and a transformation is applied to replace at least one note in the first set of notes with at least one note in a second set of notes. The transformation may explore or call upon the full range of musical notes available without being constrained by conventions of musicality and harmony. For each particular note in the second set of notes that replaces a note in the first set of notes, whether the particular note is in musical harmony with other notes in the music data object is separately assessed and, if not, the particular note is adjusted to bring it into musical harmony with other notes in the music data object.

Computer-based systems, devices, and methods for generating musical compositions are described. A population of musical compositions stored in digital media are each segmented to produce abridged samples. The samples are analyzed to identify “parent” compositions that best exhibit or evoke a particular desired quality. The parent compositions are cross-bred to generate a set of child compositions which are similarly segmented and analyzed. The child compositions that best exhibit or evoke the particular desired quality are re-cast as parent compositions from which another generation of child compositions are bred. Mutations in the form of musical variations are inserted in at least some iterations and the process is repeated until at least one child composition that satisfies some exit criterion is returned.

Computer-based systems, devices, and methods for generating musical note sequences are described. One or more musical composition(s) stored in digital media include one or more data object(s) that encode notes and/or note sequences. At least one note sequence is processed to form a time-ordered sequence of parallel notes, which is analyzed to determine a k-back probability transition matrix for the at least one note sequence. An attribute, such as a style, of the at least one note sequence is thus encoded and used to generate new note sequences that embody a similar attribute or style. In some implementations, the at least one note sequence may include a concatenated set of note sequences representative of a particular library of musical compositions.