Examples of wearable devices that can present to a user of the display device an audible or visual representation of an audio file comprising a plurality of stem tracks that represent different audio content of the audio file are described. Systems and methods are described that determine the pose of the user; generate, based on the pose of the user, an audio mix of at least one of the plurality of stem tracks of the audio file; generate, based on the pose of the user and the audio mix, a visualization of the audio mix; communicate an audio signal representative of the audio mix to the speaker; and communicate a visual signal representative of the visualization of the audio mix to the display.

A voice synthesis device includes at least one processor, implementing a first voice model and a second voice model different from the first voice model, the at least one processor performing the following: receiving data indicating a specified pitch; and causing the first voice model to output a first data and the second voice model to output a second data, and generating and outputting a third data corresponding to the specified pitch based on the first data and second data.

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.

A media-content augmentation system includes a processing system that receives input data in the form of temporally-varying events data. The processing system resolves the input into one or more categorized contextual themes, correlates the themes with metadata associated with at least one reference media file, and then splices or fades together selected parts of the media file, thus generating as an output, a media product in which transitions between its contextual themes are aligned with selected temporal events in the input data. The temporarily-varying events take the form of a beginning and an end in the case of a sustained feature, or a specific point in time for a hit point. A method aligns sections in digital media files with temporally-varying events data to compose a media product. The system augments a sensory experience of a user by dynamically changing and then playing selected media files within the context of the categorized themes input to the processing system.

The present disclosure provides a method for mixing audio, pertaining to the technical field of multimedia. The method includes: after acquiring an audio material to be mixed, determining a beat feature of a target audio, performing beat adjustment on the audio material based on the beat feature of the target audio; and performing audio mixing on the target audio based on the audio material adjusted by the beat adjustment.

An information processing apparatus (100) according to the present disclosure includes an acquiring unit (132) that uses a trained encoder to acquire a feature value of each set of partial data forming first content; a calculating unit (133) that calculates a relative feature value that is a relative feature value between sets of partial data from the acquired feature values of the sets of partial data to calculate a relative feature value sequence indicating a feature of a structure of the first content; and a generating unit (134) that generates second content based on the relative feature value sequence of the first content and a feature value of optional data.

Musical catalog amplification services that leverage or deploy a computer-based musical composition system are described. The computer-based musical composition system employs algorithms and, optionally, artificial intelligence to generate new music based on analyses of existing music. The new music may be wholly distinctive from, or may include musical variations of, the existing music. Rights in the new music generated by the computer-based musical composition system are granted to the rights holder(s) of the existing music. In this way, the musical catalog(s) of the rights holder(s) is/are amplified to include additional music assets. The computer-based musical composition system may be tuned so that the new music sounds more like, or less like, the existing music of the rights holder(s). Revenues generated from the new music are shared between the musical catalog amplification service provider and the rights holder(s).

Computer-based systems, devices, and methods for assigning mood labels to musical compositions are described. A mood classifier is trained based on mood-labeled musically-coherent segments of musical compositions and subsequently applied to automatically assign mood labels to musically-coherent segments of musical compositions. In both cases, the musically-coherent segments are generated using automated segmentation algorithms.

Computer-based systems, devices, and methods for generating variations of musical compositions are described. Musical compositions stored in digital media include one or more music data object(s) that encode notes. A first set of notes is characterized and a transformation is applied to replace at least one note in the first set of notes with at least one note in a second set of notes. The transformation may explore or call upon the full range of musical notes available without being constrained by conventions of musicality and harmony. For each particular note in the second set of notes that replaces a note in the first set of notes, whether the particular note is in musical harmony with other notes in the music data object is separately assessed and, if not, the particular note is adjusted to bring it into musical harmony with other notes in the music data object.

Computer-based systems, devices, and methods for generating musical compositions are described. A population of musical compositions stored in digital media are each segmented to produce abridged samples. The samples are analyzed to identify “parent” compositions that best exhibit or evoke a particular desired quality. The parent compositions are cross-bred to generate a set of child compositions which are similarly segmented and analyzed. The child compositions that best exhibit or evoke the particular desired quality are re-cast as parent compositions from which another generation of child compositions are bred. Mutations in the form of musical variations are inserted in at least some iterations and the process is repeated until at least one child composition that satisfies some exit criterion is returned.