Adobe, Inc.

Microsoft Technology Licensing, LLC

University of California

New York University

Lubomira A Dontcheva

Aseem Agarwala

Joel Richard Brandt

Hijung Shin

Seth John Walker

Dingzeyu Li

Joy Oakyung Kim

Xue Bai

Jovan Popović

Cristin Ailidh Fraser

Gregg Darryl Wilensky

Walter Chang

Kim Pascal Pimmel

Wilmot Wei-Mau Li

Justin Salamon

Gierad P Laput

Alan Wilson

Zhicheng Liu

Zhengyang Ma

Xuecong Xu

Pankaj Kumar Nathani

Anh Lan Truong

Kyratso George Karahalios

Eytan Adar

Timothy Jeewun Ganter

Arjun Srinivasan

Haoran Cai

Jui-hsien Wang

Aaron Phillip Hertzmann

Holger Winnemoeller

Wilmot Li

Fabian David Caba Heilbron

Jian Zhao

Hanieh Deilamsalehy

Morgan Dixon

Steven Mark Drucker

Michael F Cohen

Lubomir D Bourdev

Li-Yi Wei

Shmuel Avidan

Zhihong Ding

Niloy Jyoti Mitra

Kent Andrew Edmonds

Benoit Gerard Ambry

Stephen Diverdi

John Nelson

Matthew Douglas Hoffman

Deepali Aneja

Christopher Nuuja

Ranjitha S Kumar

David R Stein

Darshan D Prasad

Morgan Nicole Evans

Najika Skyler Halsema Yoo

William Hayes Allen

Haiqing Lu

Zachary Platt McCullough

Jiaju Ma

Rubaiat Habib

James Hennessey

Jasper O'Leary

Scott Klemmer

Adrian Joseph Secord

Claudia Veronica Roberts

Hariharan Subramonyam

Suporn Pongnumkul

Amanda Marie Swearngin

Holger Winnemöller

Daniel C Ritchie

Embodiments of the present invention provide systems, methods, and computer storage media for a visual and text search interface used to navigate a video transcript. In an example embodiment, a freeform text query triggers a visual search for frames of a loaded video that match the freeform text query (e.g., frame embeddings that match a corresponding embedding of the freeform query), and triggers a text search for matching words from a corresponding transcript or from tags of detected features from the loaded video. Visual search results are displayed (e.g., in a row of tiles that can be scrolled to the left and right), and textual search results are displayed (e.g., in a row of tiles that can be scrolled up and down). Selecting (e.g., clicking or tapping on) a search result tile navigates a transcript interface to a corresponding portion of the transcript.

Visual and text search interface for text-based video editing

Embodiments of the present invention provide systems, methods, and computer storage media for selection of the best image of a particular speaker's face in a video, and visualization in a diarized transcript. In an example embodiment, candidate images of a face of a detected speaker are extracted from frames of a video identified by a detected face track for the face, and a representative image of the detected speaker's face is selected from the candidate images based on image quality, facial emotion (e.g., using an emotion classifier that generates a happiness score), a size factor (e.g., favoring larger images), and/or penalizing images that appear towards the beginning or end of a face track. As such, each segment of the transcript is presented with the representative image of the speaker who spoke that segment and/or input is accepted changing the representative image associated with each speaker.

Speaker thumbnail selection and speaker visualization in diarized transcripts for text-based video

Embodiments of the present invention provide systems, methods, and computer storage media for segmenting a transcript into paragraphs. In an example embodiment, a transcript is segmented to start a new paragraph whenever there is a change in speaker and/or a long pause in speech. If any remaining paragraphs are longer than a designated length or duration (e.g., 50 or 100 words), each of those paragraphs is segmented using dynamic programming to minimize a cost function that penalizes candidate paragraphs based on divergence from a target paragraph length and/or that rewards candidate paragraphs that group semantically similar sentences. As such, the transcript is visualized, segmented at the identified paragraphs.

Transcript paragraph segmentation and visualization of transcript paragraphs

Embodiments of the present invention provide systems, methods, and computer storage media for music-aware speaker diarization. In an example embodiment, one or more audio classifiers detect speech and music independently of each other, which facilitates detecting regions in an audio track that contain music but do not contain speech. These music-only regions are compared to the transcript, and any transcription and speakers that overlap in time with the music-only regions are removed from the transcript. In some embodiments, rather than having the transcript display the text from this detected music, a visual representation of the audio waveform is included in the corresponding regions of the transcript.

Music-aware speaker diarization for transcripts and text-based video editing

Embodiments of the present disclosure provide, a method, a system, and a computer storage media that provide mechanisms for multimedia effect addition and editing support for text-based video editing tools. The method includes generating a user interface (UI) displaying a transcript of an audio track of a video and receiving, via the UI, input identifying selection of a text segment from the transcript. The method also includes in response to receiving, via the UI, input identifying selection of a particular type of text stylization or layout for application to the text segment. The method further includes identifying a video effect corresponding to the particular type of text stylization or layout, applying the video effect to a video segment corresponding to the text segment, and applying the particular type of text stylization or layout to the text segment to visually represent the video effect in the transcript.

Video editing using transcript text stylization and layout

Display screen or portion thereof with graphical user interface

Embodiments of the present invention provide systems, methods, and computer storage media for face-aware speaker diarization. In an example embodiment, an audio-only speaker diarization technique is applied to generate an audio-only speaker diarization of a video, an audio-visual speaker diarization technique is applied to generate a face-aware speaker diarization of the video, and the audio-only speaker diarization is refined using the face-aware speaker diarization to generate a hybrid speaker diarization that links detected faces to detected voices. In some embodiments, to accommodate videos with small faces that appear pixelated, a cropped image of any given face is extracted from each frame of the video, and the size of the cropped image is used to select a corresponding active speaker detection model to predict an active speaker score for the face in the cropped image.

Face-aware speaker diarization for transcripts and text-based video editing

Embodiments of the present invention provide systems, methods, and computer storage media for identifying candidate boundaries for video segments, video segment selection using those boundaries, and text-based video editing of video segments selected via transcript interactions. In an example implementation, boundaries of detected sentences and words are extracted from a transcript, the boundaries are retimed into an adjacent speech gap to a location where voice or audio activity is a minimum, and the resulting boundaries are stored as candidate boundaries for video segments. As such, a transcript interface presents the transcript, interprets input selecting transcript text as an instruction to select a video segment with corresponding boundaries selected from the candidate boundaries, and interprets commands that are traditionally thought of as text-based operations (e.g., cut, copy, paste) as an instruction to perform a corresponding video editing operation using the selected video segment.

Video segment selection and editing using transcript interactions

A framework for generating and presenting verbal command suggestions to facilitate discoverability of commands capable of being understood and support users exploring available commands. A target associated with a direct-manipulation input is received from a user via a multimodal user interface. A set of operations relevant to the target is selected and verbal command suggestions relevant to the selected set of operations and the determined target are generated. At least a portion of the generated verbal command suggestions is provided for presentation in association with the multimodal user interface in one of three interface variants: one that presents command suggestions as a list, one that presents command suggestions using contextual overlay windows, and one that presents command suggestions embedded within the interface. Each of the proposed interface variants facilitates user awareness of verbal commands that are capable of being executed and teaches users how available verbal commands can be invoked.

Facilitating discovery of verbal commands using multimodal interfaces

Embodiments are directed to a snap point segmentation that defines the locations of selection snap points for a selection of video segments. Candidate snap points are determined from boundaries of feature ranges of the video indicating when instances of detected features are present in the video. In some embodiments, candidate snap point separations are penalized for being separated by less than a minimum duration corresponding to a minimum pixel separation between consecutive snap points on a video timeline. The snap point segmentation is computed by solving a shortest path problem through a graph that models different snap point locations and separations. When a user clicks or taps on the video timeline and drags, a selection snaps to the snap points defined by the snap point segmentation. In some embodiments, the snap points are displayed during a drag operation and disappear when the drag operation is released.

Snap point video segmentation identifying selection snap points for a video

Embodiments are directed to segmentation and hierarchical clustering of video. In an example implementation, a video is ingested to generate a multi-level hierarchical segmentation of the video. In some embodiments, the finest level identifies a smallest interaction unit of the video—semantically defined video segments of unequal duration called clip atoms. Clip atom boundaries are detected in various ways. For example, speech boundaries are detected from audio of the video, and scene boundaries are detected from video frames of the video. The detected boundaries are used to define the clip atoms, which are hierarchically clustered to form a multi-level hierarchical representation of the video. In some cases, the hierarchical segmentation identifies a static, pre-computed, hierarchical set of video segments, where each level of the hierarchical segmentation identifies a complete set (i.e., covering the entire range of the video) of disjoint (i.e., non-overlapping) video segments with a corresponding level of granularity.

Hierarchical segmentation based on voice-activity

Embodiments are directed to techniques for interacting with a hierarchical video segmentation using a metadata panel with a composite list of video metadata. The composite list is segmented into selectable metadata segments at locations corresponding to boundaries of video segments defined by a hierarchical segmentation. In some embodiments, the finest level of a hierarchical segmentation identifies the smallest interaction unit of a video—semantically defined video segments of unequal duration called clip atoms, and higher levels cluster the clip atoms into coarser sets of video segments. One or more metadata segments can be selected in various ways, such as by clicking or tapping on a metadata segment or by performing a metadata search. When a metadata segment is selected, a corresponding video segment is emphasized on the video timeline, a playback cursor is moved to the first video frame of the video segment, and the first video frame is presented.

Interacting with hierarchical clusters of video segments using a metadata panel

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San Francisco, CA, United States of America

Lubomira A Dontcheva