Presentation assessment and valuation system

    公开(公告)号:US12236798B2

    公开(公告)日:2025-02-25

    申请号:US16151226

    申请日:2018-10-03

    Applicant: eduPresent LLC

    Abstract: A computer implemented interactive presentation assessment and valuation system which provides a server computer that allows one or more computing devices to access a presentation assessment and valuation system which provides a presentation analyzer which applies standardized scoring algorithms to the video data or audio data associated with a presentation and correspondingly generates standardized word rate, word clarity, filler words, tone, or eye contact scores, and calculates a presentation score based upon an average or weighted average of the scores.

    Personalized text proofing using distributed services

    公开(公告)号:US12236189B2

    公开(公告)日:2025-02-25

    申请号:US17502933

    申请日:2021-10-15

    Abstract: Systems and methods are directed to providing personalized text proofing. A user model that is used to personalize generic critiques for text proofing a document is generated based on user signals indicating past user actions. During runtime of an application used to create the document, the user model is accessed and locally cached. User inputs comprising typed components used to create the document are received and a set of one or more generic critiques for the user inputs is accessed from an editor system. The user model is applied to the set which may modify a generic critique of the set. The modifying of the generic critique can cause the generic critique to be automatically applied or suppressed at the client device. The set including the modified generic critique is transmitted to a user device, whereby the user device applies the set to the document including automatically applying or suppressing the modified generic critique.

    Techniques and models for multilingual text rewriting

    公开(公告)号:US12210848B2

    公开(公告)日:2025-01-28

    申请号:US17682282

    申请日:2022-02-28

    Applicant: Google LLC

    Abstract: The technology provides a model-based approach for multilingual text rewriting that is applicable across many languages and across different styles including formality levels or other textual attributes. The model is configured to manipulate both language and textual attributes jointly. This approach supports zero-shot formality-sensitive translation, with no labeled data in the target language. An encoder-decoder architectural approach with attribute extraction is used to train rewriter models that can thus be used in “universal” textual rewriting across many different languages. A cross-lingual learning signal can be incorporated into the training approach. Certain training processes do not employ any exemplars. This approach enables not just straight translation, but also the ability to create new sentences with different attributes.

    CONTEXT-BASED DECODER CORRECTION
    5.
    发明申请

    公开(公告)号:US20240419895A1

    公开(公告)日:2024-12-19

    申请号:US18209890

    申请日:2023-06-14

    Abstract: Disclosed in some examples are methods, systems, and machine-readable mediums for utilizing context information to create decoding feedback information to improve decoder accuracy and/or performance. In some examples, the context information is from layers of a network stack above the layers in which the decoders are present. The context information may be or be based upon information about previously received and decoded data and/or information about the sender to provide decoding feedback information to the decoder that is used either to correct a previous decoding error or to inform the decoder on which of a plurality of decoding choices is more likely to be correct. This may increase decoding performance by decreasing errors and in some examples, reducing the complexity of choices by eliminating certain decoding possibilities and thus increasing decoder efficiency.

    Filler word detection through tokenizing and labeling of transcripts

    公开(公告)号:US12169691B2

    公开(公告)日:2024-12-17

    申请号:US18295684

    申请日:2023-04-04

    Applicant: Descript, Inc.

    Abstract: Introduced here are computer programs and associated computer-implemented techniques for discovering the presence of filler words through tokenization of a transcript derived from audio content. When audio content is obtained by a media production platform, the audio content can be converted into text content as part of a speech-to-text operation. The text content can then be tokenized and labeled using a Natural Language Processing (NLP) library. Tokenizing/labeling may be performed in accordance with a series of rules associated with filler words. At a high level, these rules may examine the text content (and associated tokens/labels) to determine whether patterns, relationships, verbatim, and context indicate that a term is a filler word. Any filler words that are discovered in the text content can be identified as such so that appropriate action(s) can be taken.

    CONSTRUCTING DIGITAL DESIGN GRAPHS FOR GENERATING STRUCTURAL REPRESENTATIONS OF DIGITAL DESIGN DOCUMENTS

    公开(公告)号:US20240403557A1

    公开(公告)日:2024-12-05

    申请号:US18328286

    申请日:2023-06-02

    Applicant: Adobe Inc.

    Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that generates a design representation to further construct a digital design multigraph and generate a structural representation for a digital design document from the digital design multigraph. For instance, the disclosed systems generate a design representation of a digital design document that includes design properties with multiple digital design elements. In particular, the disclosed systems construct a digital design (multi-) graph from the design representation by generating nodes to represent digital design elements and edges based on relationships between these elements. In addition, the disclosed systems generate a structural representation based on the digital design multigraph for downstream applications. For instance, downstream applications include utilizing the structural representation to select a resizing model from a plurality of resizing models and resizing a digital design document using the structural representation.

    Automatic tone detection and suggestion

    公开(公告)号:US12153893B2

    公开(公告)日:2024-11-26

    申请号:US17583909

    申请日:2022-01-25

    Abstract: A method and system for providing tone detection for a content may include receiving a request to detect a tone for a content, retrieving user data and data about the content, detecting a content environment for the content based on at least one of the user data and the data about the content, detecting the tone for the content based on the content and the content environment, inputting the content and the detected tone into a machine-learning (ML) model for modifying the tone from the detected tone to a modified tone, obtaining at least one rephrased content segment as an output from the ML model, the rephrased content segment modifying the tone of the content from the detected tone to the modified tone, and providing at least one of the detected tone or the at least one rephrased content segment for display.

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