The present disclosure relates to a system and method for matching performance with score. The method may include acquiring performance information in a preset time period, wherein the performance information is related to a musical device. The method may also include analyzing the performance information and obtaining a played music score in the preset time period, wherein the played music score contains the performance information. The method may further include comparing the played music score with one or more standard music scores. The method may still further include identifying a standard music score from the one or more standard music score based on the comparison of the played music score with the one or more standard music scores, wherein a matching degree between the played music score and the identified standard music score reaches a preset value.

A performance analysis method realized by a computer includes sequentially estimating performance positions within a musical piece by an analysis process applied to an audio signal representing a performance sound of the musical piece, and setting a performance position at a first time point on a time axis within the musical piece to a performance position corresponding to a time series of the performance positions estimated by the analysis process in a selection period prior to and spaced away from the first time point within the musical piece.

The present invention is designed to allow easy synchronization of the movement of a computer graphics (CG) model with sound data. The data structure according to an embodiment of the present invention presents a data structure that relates to a computer graphics (CG) model, including first time-series information for designating the coordinates of the components of the CG model on a per beat basis, and the first time-series information is used on a computer to process the CG model.

A parameter inference method realized by a computer, includes obtaining target performance information indicating a performance of music using an electronic musical instrument; inferring assist information from the target performance information with use of a trained inference model generated through machine learning, the assist information being related to setting of a parameter of the electronic musical instrument that conforms to a tendency of the performance; and outputting the inferred assist information related to the setting of the parameter.

An information processing method according to the present invention includes providing first musical piece information representing contents of a musical piece and performance information relating to a past performance prior to one unit period within the musical piece to a learner that has undergone learning relating to a specific tendency that relates to a performance, and generating, for the one unit period, performance information that is based on the specific tendency with the learner.

A method and system for teaching oneself to learn to play a string instrument and master it by analyzing ones real-time hand/finger movement/technique/form, enabling oneself to progress and correct ones own mistakes simultaneously. In one aspect, a system for learning to play a string instrument is provided that includes a simulation instrument that includes a plurality of strings, wherein at least one of the strings includes at least one-touch sensing sensor thereon in communication with at least one processor to receive a signal from the at least one touch-sensing sensor and determine therefrom when and where on the at least one string a user applies pressure to the at least one string.

A portable digital audio system for a musician. The digital audio system includes an amplifier for processing an audio signal from a musical instrument or microphone electronically connected to the digital audio system and a speaker for playing a sound associated with the audio signal processed by the amplifier. The portable digital audio system also includes an audio control system providing operational control of the digital audio system and a primary housing for supporting the amplifier, the audio control system, and the speaker. Further, the digital audio system has a touch screen display in electronic communication with the audio control system and supported by the primary housing.

A trained model establishment method realized by a computer includes acquiring a plurality of datasets each of which is formed by a combination of first performance data of a first performance by a performer, second performance data of a second performance performed together with the first performance, and a satisfaction label indicating a degree of satisfaction of the performer, and executing machine learning of a satisfaction estimation model by using the plurality of datasets. In the machine learning, the satisfaction estimation model is trained such that, for each of the datasets, a result of estimating a degree of satisfaction the performer from the first performance data and the second performance data matches the degree of the satisfaction indicated by the satisfaction label.

A performance agent training method realized by at least one computer includes observing a first performance of a musical piece by a performer, generating, by a performance agent, performance data of a second performance to be performed in parallel with the first performance, outputting the performance data such that the second performance is performed in parallel with the first performance of the performer, acquiring a degree of satisfaction of the performer with respect to the second performance performed based on the output performance data, and training the performance agent by reinforcement learning, using the degree of satisfaction as a reward.

A computer-implemented method includes obtaining a trained model trained to store a relationship between first performance information and evaluation information. The first performance information includes a plurality of performance units. The evaluation information includes a plurality of pieces of evaluation information respectively associated with the plurality of performance units. The method also includes obtaining second performance information including an evaluation of each performance unit of the plurality of performance units. The method also includes processing the second performance information using the trained model to infer the evaluation of the each performance unit.