G10H2210/565

Cognitive music engine using unsupervised learning

A method for generating a musical composition based on user input is described. A first set of musical characteristics from a first input musical piece is received as an input vector. The first set of musical characteristics is perturbed to create a perturbed input vector as input in a first set of nodes in a first visible layer of an unsupervised neural net. The unsupervised neural net comprised of a plurality of computing layers, each computing layer composed of a respective set of nodes. The unsupervised neural net is operated to calculate an output vector from a higher level hidden layer in the unsupervised neural net. The output vector is used to create an output musical piece.

SYSTEMS AND METHODS FOR ONBOARD, REAL-TIME PICKUP BLENDING FOR ELECTRIC GUITARS AND BASSES
20230049331 · 2023-02-16 ·

Systems and methods for onboard, real-time pickup blending for electric guitars/basses may utilize every possible tonal combination that double coil pickups can offer. The industry standard pickup toggle switch may be removed from electric guitar/bass instruments. Instead of a user being limited to only using one pickup at a time to be selected, the user may mix in any combination of the pickups (top, bottom, or both) at any time. Accordingly, multiple pickups can be on at the same time and/or the user may blend in (or out) any percentage of any of the pickups that the user wishes to create a large combination of tones.

AUTOMATED GENERATION OF AUDIO TRACKS
20230197042 · 2023-06-22 ·

Conventionally, significant time and effort are required to construct audio tracks. Disclosed embodiments enable automation of audio tracks using templates that associate sound generator(s) with template section(s). Each template enables a model to automatically generate unique audio tracks in which the sections and/or sounds are probabilistically determined. Certain embodiments introduce additional variability into the automated generation of audio tracks. In addition, the model may generate the audio tracks, note by note, to ensure that no copyrights are infringed.

System for generating and implementing digital music tuning files
11727906 · 2023-08-15 · ·

A system and method to generate and implement digital tuning files based on p-smooth number sequences for use with a digital musical instrument is provided. A p-smooth number sequence is generated and a subset of p-smooth numbers from the sequence is chosen as a musical octave of musical note frequencies. Each note within the octave is designated as a tonic, and each tonic is used to generate additional musical octaves and corresponding musical note notations. The musical octaves and corresponding musical note notations are stored into the digital memory of the digital musical instrument, and the instrument's native musical note mappings are remapped to the musical octaves and corresponding musical note notations from the digital file.

Systems and methods for onboard, real-time pickup blending for electric guitars and basses
11817072 · 2023-11-14 ·

Systems and methods for onboard, real-time pickup blending for electric guitars/basses may utilize every possible tonal combination that double coil pickups can offer. The industry standard pickup toggle switch may be removed from electric guitar/bass instruments. Instead of a user being limited to only using one pickup at a time to be selected, the user may mix in any combination of the pickups (top, bottom, or both) at any time. Accordingly, multiple pickups can be on at the same time and/or the user may blend in (or out) any percentage of any of the pickups that the user wishes to create a large combination of tones.

Systems and methods for onboard, real-time pickup blending for electric guitars and basses
11276381 · 2022-03-15 ·

Systems and methods for onboard, real-time pickup blending for electric guitars/basses may utilize every possible tonal combination that double coil pickups can offer. The industry standard pickup toggle switch may be removed from electric guitar/bass instruments. Instead of a user being limited to only using one pickup at a time to be selected, the user may mix in any combination of the pickups (top, bottom, or both) at any time. Accordingly, multiple pickups can be on at the same time and/or the user may blend in (or out) any percentage of any of the pickups that the user wishes to create a large combination of tones.

Systems and Methods for Onboard, Real-Time Pickup Blending for Electric Guitars and Basses
20240046906 · 2024-02-08 ·

A system and a kit can be used for onboard, real-time blending for electronic pickups to produce various tonal combinations. In one example, at least one of the electronic pickups has dual coils. The dual coil pickup can be electrically connected to a switching circuit positioned on a stringed instrument. The switching circuit can be adjustable in real-time to select between at least two conditions for a signal of the dual coil pickup. In one instance, the conditions can select north coil only, series wiring of the dual coils, or south coil only. Alternatively, the conditions can select series wiring or parallel wiring of the dual coils. Each of the electronic pickups is electrically connected to a taper circuit positioned on the instrument. Each taper circuit is adjustable in real-time to vary an amplitude of the signal from the respective electronic pickup for output of the instrument.

COGNITIVE MUSIC ENGINE USING UNSUPERVISED LEARNING
20190304419 · 2019-10-03 ·

A method for generating a musical composition based on user input is described. A first set of musical characteristics from a first input musical piece is received as an input vector. The first set of musical characteristics is perturbed to create a perturbed input vector as input in a first set of nodes in a first visible layer of an unsupervised neural net. The unsupervised neural net comprised of a plurality of computing layers, each computing layer composed of a respective set of nodes. The unsupervised neural net is operated to calculate an output vector from a higher level hidden layer in the unsupervised neural net. The output vector is used to create an output musical piece.

Cognitive music engine using unsupervised learning

A method for generating a musical composition based on user input is described. A first set of musical characteristics from a first input musical piece is received as an input vector. The first set of musical characteristics is perturbed to create a perturbed input vector as input in a first set of nodes in a first visible layer of an unsupervised neural net. The unsupervised neural net comprised of a plurality of computing layers, each computing layer composed of a respective set of nodes. The unsupervised neural net is operated to calculate an output vector from a higher level hidden layer in the unsupervised neural net. The output vector is used to create an output musical piece.

System for generating and implementing digital music tuning files
12020673 · 2024-06-25 · ·

A system and method to generate and implement digital tuning files based on p-smooth number sequences for use with a digital musical instrument is provided. A p-smooth number sequence is generated and a subset of p-smooth numbers from the sequence is chosen as a musical octave of musical note frequencies. Each note within the octave is designated as a tonic, and each tonic is used to generate additional musical octaves and corresponding musical note notations. The musical octaves and corresponding musical note notations are stored into the digital memory of the digital musical instrument, and the instrument's native musical note mappings are remapped to the musical octaves and corresponding musical note notations from the digital file.