Abstract: Vocal audio of a user together with performance synchronized video is captured and coordinated with audiovisual contributions of other users to form composite duet-style or glee club-style or window-paned music video-style audiovisual performances. In some cases, the vocal performances of individual users are captured (together with performance synchronized video) on mobile devices, television-type display and/or set-top box equipment in the context of karaoke-style presentations of lyrics in correspondence with audible renderings of a backing track. Contributions of multiple vocalists are coordinated and mixed in a manner that selects for presentation, at any given time along a given performance timeline, performance synchronized video of one or more of the contributors. Selections are in accord with a visual progression that codes a sequence of visual layouts in correspondence with other coded aspects of a performance score such as pitch tracks, backing audio, lyrics, sections and/or vocal parts.

Abstract: Digital signal processing and machine learning techniques can be employed in a vocal capture and performance social network to computationally generate vocal pitch tracks from a collection of vocal performances captured against a common temporal baseline such as a backing track or an original performance by a popularizing artist. In this way, crowd-sourced pitch tracks may be generated and distributed for use in subsequent karaoke-style vocal audio captures or other applications. Large numbers of performances of a song can be used to generate a pitch track. Computationally determined pitch trackings from individual audio signal encodings of the crowd-sourced vocal performance set are aggregated and processed as an observation sequence of a trained Hidden Markov Model (HMM) or other statistical model to produce an output pitch track.

Abstract: Audiovisual performances, including vocal music, are captured and coordinated with those of other users in ways that create compelling user experiences. In some cases, the vocal performances of individual users are captured (together with performance synchronized video) on mobile devices, television-type display and/or set-top box equipment in the context of karaoke-style presentations of lyrics in correspondence with audible renderings of a backing track. Contributions of multiple vocalists are coordinated and mixed in a manner that selects for visually prominent presentation performance synchronized video of one or more of the contributors. Prominence of particular performance synchronized video may be based, at least in part, on computationally-defined audio features extracted from (or computed over) captured vocal audio.

Abstract: Despite many practical limitations imposed by mobile device platforms and application execution environments, vocal musical performances may be captured and continuously pitch-corrected for mixing and rendering with backing tracks in ways that create compelling user experiences. In some cases, the vocal performances of individual users are captured on mobile devices in the context of a karaoke-style presentation of lyrics in correspondence with audible renderings of a backing track. Such performances can be pitch-corrected in real-time at a portable computing device (such as a mobile phone, personal digital assistant, laptop computer, notebook computer, pad-type computer or netbook) in accord with pitch correction settings. In some cases, pitch correction settings include a score-coded melody and/or harmonies supplied with, or for association with, the lyrics and backing tracks.

Abstract: Captured vocals may be automatically transformed using advanced digital signal processing techniques that provide captivating applications, and even purpose-built devices, in which mere novice user-musicians may generate, audibly render and share musical performances. In some cases, the automated transformations allow spoken vocals to be segmented, arranged, temporally aligned with a target rhythm, meter or accompanying backing tracks and pitch corrected in accord with a score or note sequence. Speech-to-song music applications are one such example. In some cases, spoken vocals may be transformed in accord with musical genres such as rap using automated segmentation and temporal alignment techniques, often without pitch correction. Such applications, which may employ different signal processing and different automated transformations, may nonetheless be understood as speech-to-rap variations on the theme.

Abstract: Vocal musical performances may be captured and, in some cases or embodiments, pitch-corrected and/or processed in accord with a user selectable vocal effects schedule for mixing and rendering with backing tracks in ways that create compelling user experiences. In some cases, the vocal performances of individual users are captured on mobile devices in the context of a karaoke-style presentation of lyrics in correspondence with audible renderings of a backing track. Such performances can be pitch-corrected in real-time at the mobile device in accord with pitch correction settings. Vocal effects schedules may also be selectively applied to such performances. In these ways, even amateur user/performers with imperfect pitch are encouraged to take a shot at “stardom” and/or take part in a game play, social network or vocal achievement application architecture that facilitates musical collaboration on a global scale and/or, in some cases or embodiments, to initiate revenue generating in-application transactions.

Abstract: Notwithstanding practical limitations imposed by mobile device platforms and applications, truly captivating musical instruments may be synthesized in ways that allow musically expressive performances to be captured and rendered in real-time. Synthetic musical instruments that provide a game, grading or instructional mode are described in which one or more qualities of a user's performance are assessed relative to a musical score. By providing a range of modes (from score-assisted to fully user-expressive), user interactions with synthetic musical instruments are made more engaging and tend to capture user interest over generally longer periods of time. Synthetic musical instruments are described in which force dynamics of user gestures (such as finger contact forces applied to a multi-touch sensitive display or surface and/or the temporal extent and applied pressure of sustained contact thereon) are captured and drive the digital synthesis in ways that enhance expressiveness of user performances.