A method and system for shaping the tone by modular circuit bending and modding of electric and electronic music instruments, audio amplifiers and sound equipment. The design of the system consists of a modding structure of a plurality of inserts, inputs and outputs connections for compatible modules, to reconfigure the electronic circuit without the physical changing of component values and without adding or removing electronic parts of the audio equipment by soldering. A plurality of tone modules for shaping the sound by the intervention into the signal path and a plurality of modules for shaping the tone by other sound design methods that are not part of the signal path are provided. For the modular system, an external device can be used as a multiplier, which consists of a plurality of inserts, inputs and outputs connections for compatible modules also including a plurality of combined series/parallel circuits of freely selectable inputs and outputs for the direct swap of a plurality of modding modules. In addition, switching options are available to control bypass, for advanced series or parallel connections, and for AB testing capabilities. The modular modding system can be used as a standalone device or as an upgrade to existing equipment.

The present invention provides a method for processing audio data, comprising the steps of providing input audio data containing a mixture of audio data including first audio data of a first musical timbre and second audio data of a second musical timbre different from said first musical timbre, decomposing the input audio data to provide decomposed data representative of the first audio data, transforming the decomposed data to obtain third audio data.

Devices, systems and methods related to causing an apparatus to generate music information of audio data using a transformer-based neural network model with a multilevel transformer for audio analysis, using a spectral and a temporal transformer, are disclosed herein. The processor generates a time-frequency representation of obtained audio data to be applied as input for a transformer-based neural network model; determines spectral embeddings and first temporal embeddings of the audio data based on the time-frequency representation of the audio data; determines each vector of a second frequency class token (FCT) by passing each vector of the first FCT in the spectral embeddings through the spectral transformer; determines second temporal embeddings by adding a linear projection of the second FCT to the first temporal embeddings; determines third temporal embeddings by passing the second temporal embeddings through the temporal transformer; and generates music information based on the third temporal embeddings.

This application provides a song processing method performed by a computer device. The method includes: presenting a song recording interface in response to a singing instruction triggered in a session interface of a group chat session; recording a song in response to a song recording instruction triggered in the song recording interface, and determining a reverberation effect corresponding to the recorded song; and transmitting, in response to a song transmitting instruction, a target song obtained by processing the song based on the reverberation effect to members of the group chat session, presenting a session message corresponding to the target song in the session interface, and presenting the pick-up singing function item corresponding to the target song in the session interface, the pick-up singing function item being used for implementing pick-up singing of the target song by a member of the group chat session.

In various applications, the system provides a method for processing audio signals, including: receiving, by a processor, a digital audio signal from a recorded audio file; analyzing, by the processor, the digital audio signal to identify pitch distortion caused by changes in momentary sound level; determining, by the processor, an amount of compensation of the audio signal to correct the identified pitch distortion; dynamically adjusting, by the processor, the digital audio signal by the compensation amount to correct the identified pitch distortion; and outputting, by the processor, the digital audio signal to an audio transducer device of a listener to improve a listening experience for the listener of the recorded audio file.

An electronic device, a data usage method, and an electronic device program are provided. In an electronic musical instrument, in a case where a livelock flag has been turned on by an operation on a setting key by a user, a sound data is validated or invalidated according to a usable or unusable state of the sound data stored in a content state table immediately before the livelock flag has been turned on.

An audio hub is disclosed including a plurality of daughterboards and a mainboard communicatively coupled to each of the plurality of daughterboards. Each of the plurality of daughterboards is associated with an audio channel and each audio channel is independent from the other of the audio channels associated with the other ones of the plurality of daughter boards. Further, each daughterboard includes at least one wireless transceiver operably configured to wirelessly transmit an audio signal associated with the corresponding audio channel from a musical instrument over a network to the audio playback device. The mainboard is configured so that, for each of the plurality of daughterboards, the mainboard is operable to independently modify at least one characteristic of the audio signal from the musical instrument before the audio signal is transmitted to the audio playback device.

The present disclosure relates to systems, methods, and devices for music simulation. The methods may include determining one or more simulation actions based on data associated with one or more simulation actions acquired by at least one sensor. The methods may further include determining, based on at least one of the one or more simulation actions and a mapping relationship between simulation actions and corresponding musical instruments, a simulation musical instrument that matches with the one or more simulation actions. The methods may further include determining, based on the one or more simulation actions, one or more first features associated with the simulation musical instrument. The methods may further include playing music based on the one or more first features.

A method for processing music audio data, including providing input audio data representing a first piece of music comprising a mixture of musical timbres. The method also includes decomposing the input audio data to generate at least first-timbre decomposed data representing a first timbre selected from the musical timbres of the first piece of music, and second-timbre decomposed data representing a second timbre selected from the musical timbres of the first piece of music. The method also includes applying a transport control to obtain transport controlled first-timbre decomposed data. The method also includes recombining audio data obtained from the transport controlled first-timbre decomposed data with audio data obtained from the second-timbre decomposed data to obtain recombined audio data.

A system of playing media content items determines transitions between pairs of media content items by determining desirable locations in which transitions across the pairs of media content items occur. The system uses a plurality of track features of media content items and determines such track features of each media content item associated with each of transition point candidates, such as beat positions, of that media content item. The system determines similarity in the plurality of track features between the transition point candidates of a first media content item and the transition point candidates for a second media content item being played subsequent to the first media content item. The transition points or portions of the first and second media content items are selected from the transition point candidates for the first and second media content items based on the similarity results.