Provided is an information processing device including an acquisition unit that acquires subjective evaluation information from a second user about each performance performed by at least part of a body of a first user moving, a learning unit that performs machine learning on a relationship between the each performance and the corresponding subjective evaluation information and generates relationship information between the each performance and the corresponding subjective evaluation information, and a presentation unit that presents feedback information to the second user based on the relationship information.

Systems and methods for identifying the most impactful moments or segments of music, which are those most likely to elicit a chills effect in a human listener. A digital music signal is processed using two or more objective processing metrics that measure acoustic features known to be able to elicit the chills effect. Individual detection events are identified in the output of each metric based on the output being above or below thresholds relative to the overall output. A combination algorithm aggregates concurrent detection events to generate a continuous concurrence data set of the number of concurrent detection events during the music signal, which can be calculated per beat. A phrase detection algorithm can identify impactful segments of the music based on at least one of peaks, peak-proximity, and a moving average of the continuous concurrence data.

A reference part determiner determines a reference part from a plurality of parts including at least three parts. A subject part group determiner determines a subject part group from the plurality of parts, excluding the reference part determined by the reference part determiner out of the plurality of parts as a subject part group. An acquirer acquires a change pattern of a first audio parameter value set for the reference part. A changer changes a second audio parameter value set for the subject part group determined by the subject part group determiner according to a change pattern acquired by the acquirer.

A method for generating a musical score based on user performance during playing a keyboard instrument may include detecting a status change of a plurality of execution devices of the keyboard instrument. The method may include generating a first signal according to the detected status change. The method may include generating a second signal indicating a plurality of timestamps. The method may include determining a tune of the musical score based on the first signal. The method may include determining a rhythm of the musical score based on the second signal. The method may further include generating the musical score based on the tune and the rhythm of the musical score.

The present disclosure relates to a virtual drum kit device. The virtual drum kit device includes a motion capture device and a drum sound processing device separated from each other; where, the motion capture device includes at least two drumsticks, the drumstick including a first cover body, as well as a first battery, a first control printed circuit board assembly (PCBA) board and a vibration motor which are arranged in the first cover body, the first control PCBA board being connected to the battery and the vibration motor separately, and being capable of transmitting an RF signal to the drum sound processing device according to a motion instruction captured by the drumstick, the drum sound processing device includes a second cover body, as well as a second battery and a second control PCBA board which are arranged in the second cover body.

An estimation model construction method realized by a computer includes preparing a plurality of training data that include first training data that include first feature amount data that represent a first feature amount of a performance sound of a musical instrument and first onset data that represent a pitch at which an onset exists, and second training data that include second feature amount data that represent a second feature amount of sound generated by a sound source of a type different than the musical instrument, and second onset data that represent that an onset does not exist, and constructing, by machine learning using the plurality of training data, an estimation model that estimates, from a feature amount data that represent a feature amount of a performance sound of the musical instrument, estimated onset data that represent a pitch at which an onset exists.

A facility providing technological support for the initiation, performance, and/or registration of a collaborative songwriting project is described.

Disclosed is a learning model generation method executed by a computer, including: striking a percussion instrument with a striking member to emit a musical sound; and conducting machine learning upon receiving an input of the musical sound emitted from the percussion instrument, and generating, based on the machine learning, a learning model for outputting numerical values for setting musical performance parameters for an automatic musical performance of the percussion instrument that is struck when the striking member is driven.

An electronic musical instrument includes at least one function operator associated with at least one process, and at least one processor, wherein the at least one processor executes the followings, deciding that musical performance is being performed or not in response to an operation to the at least one function operator, in response to deciding that the musical performance is being performed, executing the at least one process associated with the at least one function operator, and in response to deciding that the musical performance is not being performed, not executing the process associated with the at least one function operator, despite being operated to the at least one function operator.

The disclosed technology provides solutions for enhancing a user's experience of content playback, such as that of a user that is viewing multimedia content, such as a music video, on a mobile device. In some aspects, a process of the disclosed technology can include steps for receiving a mean energy curve associated with a sound file and dynamically modulating a brightness level of a displayed content on a display based on audio properties of the mean energy curve whereby an average brightness experienced over playback of the displayed content is equal to a default brightness of the display.