Abstract: 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.

Abstract: 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.

Abstract: A computer-implemented method includes obtaining a trained model trained to store a relationship between first performance data and first evaluation data. The first performance data indicates a performance performed by a performer. The first evaluation data indicates a first evaluation of the performance. The first evaluation has been made by an audience who has received the performance. The method also includes obtaining second performance data. The method also includes processing the second performance data using the trained model to make an inference of a second evaluation of the second performance data. The method also includes outputting second evaluation data indicating the inference of the second evaluation.

Abstract: 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.

Abstract: Provided is an information processing apparatus that generates various kinds of time series data according to a performance tendency of a user. The information processing apparatus includes an index specifying unit 22 that specifies performance tendency information that indicates a performance tendency of a performance of a musical piece by a user by inputting observational performance data X representing the performance to a learned model La and an information processing unit 23 that generates time series data Z regarding the musical piece according to the performance tendency information.

Abstract: A performance analysis method is realized by a computer and includes acquiring a time series of input data representing played pitch that is played, inputting the acquired time series of input data into an estimation model that has learned a relationship between a plurality of items of training input data representing pitch and a plurality of items of training output data representing an acoustic effect to be added to sound having the pitch, and generating a time series of output data for controlling an acoustic effect to be added to sound having the played pitch represented by the acquired time series of input data.

Abstract: A reproduction control method realized by a computer includes analyzing an actual performance of an actual performer, controlling a reproduction of a performance sound of a musical piece represented by music data in accordance with a result of the analyzing of the actual performance, and outputting a message relating to the actual performance in accordance with the result of the analyzing of the actual performance.

Abstract: An audio processing system includes at least one memory storing a program and at least one processor. The processor implements the program to analyze an audio signal including sound from a first sound source; identify, based on the analysis of the audio signal, a series of sound indicators each representing a certainty that audio components of the first sound source are included in the audio signal; identify a series of pitches, each relating to the components of the first sound source; and cause a display device to display the series of the sound indicators and the identified series of the pitches along a common time axis.

Abstract: A music analysis method includes estimating a plurality of provisional points that are candidates for a specific point that has musical meaning in a musical piece from an audio signal of the musical piece by using a first process, selecting a part of a plurality of candidate points, which include the plurality of provisional points and a plurality of division points that divide intervals between the plurality of provisional points, as a plurality of selection points, and estimating a plurality of specific points in the musical piece from a result of calculating a probability that each of the plurality of selection points is the specific point by using a second process which is different from the first process.

Abstract: A computer-implemented reproduction control method includes reproducing sound from sound data representing a series of sounds including first sound and second sound that follows the first sound. The method includes starting reproducing the first sound, continuing the reproduction of a first sound until an end of the first sound in response to receiving a first instruction in a reproduction period of the first sound, stopping the reproduction of the first sound, and after the stopping of the reproduction of the first sound, starting reproducing the second sound in response to receiving a second instruction provided by a user.

Abstract: A music analysis method realized by a computer includes calculating an evaluation index of each of a plurality of structure candidates formed of N analysis points selected in different combinations from K analysis points in an audio signal of a musical piece, and selecting one of the plurality of structure candidates as a boundary of a structure section of the musical piece in accordance with the evaluation index of each of the plurality of structure candidates. N is a natural number greater than or equal to 2 and less than K, and K is a natural number greater than or equal to 2.

Abstract: An image control system includes an estimation circuit, an obtaining circuit, and an image control circuit, which circuits can be at least one processor. The estimation circuit receives an output from a trained model in response to an input of an acoustic signal indicating a performance of a musical piece. The estimation circuit estimates musical performance information based on the output. The musical performance information is associated with the performance indicated by the acoustic signal relative to the musical piece. The obtaining circuit obtains manipulation information that is associated with a playback of an image. The image control circuit controls the playback of the image based on the musical performance information. The image control circuit controls the playback of the image based on the manipulation information upon obtaining the manipulation information.

Abstract: A musical performance correction method executable by a computer, the musical performance correction method includes: estimating a playing position in a musical composition by analyzing musical performance data indicating a played pitch played by a user; and correcting the played pitch indicated by the musical performance data to a reference pitch, from among a plurality of reference pitches corresponding to the playing position in the musical composition, in a case where a difference between the played pitch and the reference pitch is less than a predetermined value.

Abstract: An information processing method implemented by a computer, the information processing method including, generating pedal data representing an operation period of a pedal that extends sound production by key depression, from playing data representing a playing content.

Abstract: An information processing method includes generating a change parameter relating to a process in which a temporal relationship between a first motion and a second motion changes, by inputting, into a trained model, first time-series data that represent a content of the first motion, and second time-series data that represent a content of the second motion in parallel to the first motion.

Abstract: An information processing method includes generating performance data that represent a performance of a musical piece that reflects a change caused by a factor that alters the performance of the musical piece, by inputting musical score data, which represent a musical score of the musical piece, and variability data, which represent the factor, into a trained model.

Abstract: An audio processing device includes a feature extraction unit and signal generating unit. The feature extraction unit is configured to extract a feature quantity of a first audio signal for each of a plurality of periods. The signal generating unit is configured to for generate a second audio signal by time axis expanding/compressing either a section of the first audio signal in which the feature quantity is steadily maintained for a period time, or a section of the first audio signal in which a fluctuation of the feature quantity is repeated and excluding from the time axis expanding/compressing a section of the first audio signal in which a fluctuation of the feature quantity is not similar to that of other sections of the first audio signal.

Abstract: An apparatus is provided that accurately estimates a point at which a musical performance is started by a player. The apparatus includes the musical performance analysis unit 32, and the musical performance analysis unit 32 obtains action data that includes a time series of feature data representing actions made by a player during a musical performance for a reference period and estimating a sound-production point based on the action data at an estimated point using a learned model L.

Abstract: 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.

Abstract: Provided is an information processing apparatus that generates various kinds of time series data according to a performance tendency of a user. The information processing apparatus includes an index specifying unit 22 that specifies performance tendency information that indicates a performance tendency of a performance of a musical piece by a user by inputting observational performance data X representing the performance to a learned model La and an information processing unit 23 that generates time series data Z regarding the musical piece according to the performance tendency information.