Avid Technology Limited

Joseph S Plazak

Sam Butler

Robert A Gonsalves

Sylvain Girard

Samuel Lambert

Joseph A Pearson

Joseph Pearson

An operator of a digital audio workstation (DAW) application is able to assign individual tracks of a DAW session for export to specific players within a musical score of a scorewriter application. The DAW operator associates each track with a player identifier, which is retained in association with an interoperable format file generated by the export process. When the scorewriter imports such a file, it extracts the player identifier and uses it to map the track to a scored instrument. The mapping may also depend on a scorewriter arrangement of players for the instruments. The DAW operator may assign multiple tracks representing a given instrument played with different techniques to a single instrument part in a score. The playing techniques for the instruments are also associated with the tracks and may be parsed by the scorewriter to annotate the score with the corresponding notations.

Data exchange for music creation applications

A media composition application, such as a musical scorewriter or a digital audio workstation, provides in situ suggestions for continuation or completion of a media composition. The suggestions are based on some or all of the portion of the composition already composed or are based on a corpus of compositions, such as those by a particular composer or those of a specific genre. The length of the suggestions is specified by the user. The suggestions are provided within a graphical user interface of the application and displayed as a possible direct continuation of the composition within a musical stave. If the user rejects the suggestion, additional suggestions are automatically displayed in situ. Reductive, most-probable suggestions may be offered as well as exploratory suggestions that facilitate a creative compositional interaction between user and application. Data filters enable selected aspects of a data source to be used for suggestion generation.

Data-driven autosuggestion within media content creation

A graphical user interface for music creation applications, such as score notation applications and digital audio workstations, includes multi-dimensional gestures. To enter a sound event into a musical project, a user uses an input device to select and drag a desired sound event in one or more dimensions. The relative position or rate of movement along a given dimension defines a value of a sound event parameter allocated to the given dimension. The sound event is entered into the project when the selection is released. The user inputs the gesture using a pointing device such as a mouse, stylus with a touch screen, or finger on a touch screen. Stylus dimensions mapped to sound event parameters may include, horizontal and vertical stylus tip positions, vertical and horizontal tilt of the stylus, and stylus tip pressure. Sound event parameters controlled by the gestures may include diatonic pitch, chromatic inflection, and duration.

Multidimensional gestures for music creation applications

Automatic editing of media compositions is performed using media editing applications equipped with neural-network-based deep-learning models. The automatic editing is adapted to the practices of local users of a media editing application by training the models on a combination of media compositions previously edited by third-party media editors and media compositions edited by local users. Training data input vectors for the model comprise representative portions of a composition's raw media, and corresponding output vectors include values of parameters that define editing functions applied to the raw media to generate an edited media composition. A user interface enabling a user to adjust and monitor machine learning parameters is provided. Adaptive automatic editing may assist in the creation of video and audio compositions, as well as in the generation of musical scores.

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Joseph S Plazak