Aspects of the subject disclosure may include, for example, a device that has a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations including: receiving media content from user equipment, wherein the media content comprises a sample of an existing work used to modify an original work; analyzing the media content using machine learning to determine a plurality of composition parameters that characterize aspects of the media content; recording the plurality of composition parameters determined, including an identification of composition parameters in the plurality of composition parameters attributable to the existing work, and an identification of composition parameters attributable to the original work, in a blockchain ledger; searching for the composition parameters in the blockchain ledger for one or more works having similar composition parameters; and reporting any works found during the searching to the user equipment.

Disclosed herein are techniques for visualizing and configuring controller function sequences. Techniques include identifying at least one executable code segment associated with a controller; analyzing the at least one executable code segment to determine at least one function and at least one functional relationship associated with the at least one code segment; constructing, a software functionality line-of-code behavior and relation model visually depicting the determined at least one function and at least one functional relationship; displaying the software functionality line-of-code behavior and relation model at a user interface; receiving a first input at the interface; in response to the received first input, animating the line-of-code behavior and relation model to visually depict execution of the at least one executable code segment on the controller; receiving a second input at the interface; and in response to the received second input, animating an update to the line-of-code behavior and relation model.

A desktop application and supporting web site for capturing audio and video recordings or other digital content of differing modalities is introduced, wherein multiple participants in a collaborative session may be in separate remote locations. The application includes providing a high quality data format for transferring recordings, audiovisual data and the like to a remote network location or computer and a real-time data format for intercommunicating comments and instructions that are not recorded. Peer-to-peer and server-client implementations may be optimized regarding delivery time (latency) versus content quality. The desktop application also provides mechanisms for playing back sound, video or other data for participants' reference, along with synchronized presentations of textual, audio and visual material corresponding to the session.

A musical score display control method, device and program which control a processor to acquire performance data being performed, sequentially acquire performance positions of a performance in a musical score data that represent a musical score based on the musical score data and the performance data, and display on a display a predetermined portion of the musical score data according to the current performance position. The processor also controls the display to display a next performance target portion of the musical score data upon determining that the current performance position has advanced beyond a first threshold position from a prior performance position at a point in time prior to the current performance position, and to display a previous performance target portion of the musical score data upon determining that the current performance position has returned beyond a second threshold position from the prior performance position.

Systems and methods for collectively generating sound are provided. A sound composition can include multiple component pieces and those component pieces can be divided amongst devices so that the devices can collectively generate the sound composition. For example, each component piece may be assigned to a different device and the each device may provide its assigned component pieces in a synchronized manner so that the overall sound composition is collectively generated. By generating a sound composition in this manner, the network may create new and exciting spatial effects.

An electronic apparatus includes a plurality of pads, each of the plurality of pads including a touch sensor and an acceleration sensor, a sound output interface configured to output sounds that are set to the respective pads, a display configured to display visual feedback, and a processor configured to, in response to the touch sensor in a pad among the plurality of pads detecting a touch of the pad, and the acceleration sensor in the pad detecting an intensity of the touch that is greater than or equal to a value, determine that a beat is performed on the pad, control the sound output interface to output a sound that is set to the pad on which the beat is determined to be performed, with a magnitude corresponding to an intensity of the beat, and control the display to display the visual feedback corresponding to the beat determined to be performed.

In some implementations, a process for communicating data over audio is performed. In one aspect, one or more ordered sequences of audio attribute values that are selected based on a musical relationship between the audio attribute values and associated with data values may be played by a first device and received by a second device. This technique may allow for sound-based communications to take place between devices that listeners may find pleasant.

A method of synchronous recording of audio is described. The described method comprises: (a) establishing a first wireless data transmission connection between a master device and a first recording device, (b) establishing a second wireless data transmission connection between the master device and a second recording device, (c) determining a first data transmission delay for the first data transmission connection, (d) determining a second data transmission delay for the second data transmission connection, (e) transmitting predetermined reference data from the master device to the first recording device and to the second audio recording device, (f) at the first recording device: playing back the predetermined reference data and recording first recording data, and (g) at the second recording device: playing back the predetermined reference data and recording second recording data, (h) wherein during the transmission of the predetermined reference data a difference between the first data transmission delay and the second data transmission delay is taken into account in such a manner that the playing back of the predetermined reference data takes place synchronously at the first recording device and at the second recording device. Furthermore, a system for synchronously recording audio is described.

Aspects of the subject disclosure may include, for example, a device that has a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations including: receiving media content from user equipment, wherein the media content comprises a sample of an existing work used to modify an original work; analyzing the media content using machine learning to determine a plurality of composition parameters that characterize aspects of the media content; recording the plurality of composition parameters determined, including an identification of composition parameters in the plurality of composition parameters attributable to the existing work, and an identification of composition parameters attributable to the original work, in a blockchain ledger; searching for the composition parameters in the blockchain ledger for one or more works having similar composition parameters; and reporting any works found during the searching to the user equipment.

Digital signal processing and machine learning techniques can be employed in a vocal capture and performance social network to computationally generate vocal pitch tracks from a collection of vocal performances captured against a common temporal baseline such as a backing track or an original performance by a popularizing artist. In this way, crowd-sourced pitch tracks may be generated and distributed for use in subsequent karaoke-style vocal audio captures or other applications. Large numbers of performances of a song can be used to generate a pitch track. Computationally determined pitch trackings from individual audio signal encodings of the crowd-sourced vocal performance set are aggregated and processed as an observation sequence of a trained Hidden Markov Model (HMM) or other statistical model to produce an output pitch track.