Indications of sample machine learning models which create synthetic content items are provided via programmatic interfaces. A representation of a synthetic content item produced by one of the sample models in response to input obtained from a client of a provider network is presented. In response to a request from the client, a machine learning model is trained to produce additional synthetic content items.

Provided is a signal processing apparatus having: a sound source separation unit configured to perform sound source separation on a mixed sound signal obtained by mixing a plurality of sound source signals; a sound source type determination unit configured to determine a type of a predetermined sound source signal obtained by the sound source separation; and an output destination control unit configured to output the predetermined sound source signal to a corresponding output device on the basis of a determination result of the sound source type determination unit.

The present disclosure relates to an information processing apparatus, an information processing method, and a program that make it possible to adjust commonness and eccentricity of automatically generated content by likelihood exploration while satisfying reality.

Input content including a sequence of data is encoded to be converted into a latent variable, the latent variable is decoded to reconfigure output content, a loss function is calculated on the basis of a likelihood of the input content which is an input sequence, a gradient of the loss function is lowered to update the latent variable, and the updated latent variable is decoded to reconfigure output content. The present invention can be applied to an automatic content generation device.

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.

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 system, method and computer product for training a neural network system. The method comprises inputting an audio signal to the system to generate plural outputs f(X, Θ). The audio signal includes one or more of vocal content and/or musical instrument content, and each output f(X, Θ) corresponds to a respective one of the different content types. The method also comprises comparing individual outputs f(X, Θ) of the neural network system to corresponding target signals. For each compared output f(X, Θ), at least one parameter of the system is adjusted to reduce a result of the comparing performed for the output f(X, Θ), to train the system to estimate the different content types. In one example embodiment, the system comprises a U-Net architecture. After training, the system can estimate various different types of vocal and/or instrument components of an audio signal, depending on which type of component(s) the system is trained to estimate.

A system and method for media content sequencing. Prior tracks for a listening session are segmented into groups based on attribute scores for an audial attribute. A preferred group is then selected, which can be based on user feedback regarding the prior tracks in the listening session. Candidate tracks, such as from a candidate track pool for future playback in the listening session, are also segmented into the groups of the prior tracks. The candidate tracks can then be ranked based on their associated group and the preferred group.

The electronic wind instrument (1) includes an instrument body (10) in which a through-hole leading into an internal space (11) opens on an outer surface (12), an operation piece (20) attached to the instrument body (10) at a position of a through-hole (14) and pushed down toward the internal space (11), and an electronic component disposed in the internal space (11). The electronic component includes a push-down sensor (6) that detects that the operation piece (20) is being pushed down, and the outer surface (12) of the instrument body (10) comprises an outer wall (16a) that is provided around the through-hole (14) and that faces toward the through-hole (14), an inner wall (16b) that is provided nearer to the through-hole (14) than the outer wall (16a) and that faces toward the outer wall (16a), and a groove bottom (16c) connecting the outer wall (16a) and the inner wall (16b) together.

A method and apparatus for implementing a virtual performance partner are provided. The method includes collecting audio frame data performed by a performer; and for each piece of current audio frame data collected, performing: converting the piece of current audio frame data collected into a current digital score, matching the current digital score with a range of digital scores in a repertoire, and determining a matching digital score in the range of digital scores that matches the current digital score; positioning a position of the matching digital score in the repertoire, and determining a start time of playing a cooperation part of music in a next bar of the matching digital score in the repertoire for a performance partner.