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    Customized meeting notes
    2.
    发明授权
    Customized meeting notes 有权

    公开(公告)号：US11522730B2

    公开(公告)日：2022-12-06

    申请号：US17062957

    申请日：2020-10-05

    Applicant: International Business Machines Corporation

    Inventor： Ruchi Asthana ,  Jennifer A. Mallette ,  Steven Ware Jones ,  Nicholas Fong ,  Vivek Salve

    IPC: G06F40/169 ,  H04L12/18 ,  G06F40/35 ,  G06F40/289

    Abstract: In an approach to customizing meeting notes, a computer receives audio input of a virtual meeting, converts the audio input to text, and displays the text to a plurality of meeting participants. A computer receives highlighted phrases of the text from the plurality of meeting participants and determines a highlighting frequency of each of the highlighted phrases. A computer determines phrases with a highlighting frequency greater than a pre-defined threshold. A computer orders the phrases based on a chronological order of the phrases in the audio input. A computer determines preferences of a first meeting participant associated with a meeting summary. A computer generates a customized summary of the virtual meeting for the first meeting participant of the plurality of meeting participants based on the ordered phrases with a high frequency of highlighting and on the preferences. A computer transmits the customized summary to the first meeting participant.

    NOTIFICATION ESCALATION BASED ON VISUAL RECOGNITION
    4.
    发明申请
    NOTIFICATION ESCALATION BASED ON VISUAL RECOGNITION 有权

    公开(公告)号：US20220103507A1

    公开(公告)日：2022-03-31

    申请号：US17034320

    申请日：2020-09-28

    Applicant: International Business Machines Corporation

    Inventor： Lisa Lurie ,  Steven Ware Jones ,  Jennifer A. Mallette

    IPC: H04L12/58 ,  H04N7/18 ,  G08B13/196

    Abstract: A method can include obtaining notification data for a user, and obtaining a first set of images of the user from one or more cameras. The method can include identifying a first status of the user, and generating a set of notification options based on the first status. The method can include selecting a first notification option, and initiating a first notification by the first notification option. The method can include determining that the user does not acknowledge the first notification, and obtaining a second set of images from the one or more cameras. The method can include identifying a second status of the user, and selecting a second notification option of the set of notification options. The method can include initiating a second notification by the second notification option.

    TECHNOLOGY FOR CHAT BOT TRANSLATION
    5.
    发明申请
    TECHNOLOGY FOR CHAT BOT TRANSLATION 有权

    公开(公告)号：US20210184995A1

    公开(公告)日：2021-06-17

    申请号：US16711373

    申请日：2019-12-11

    Applicant: International Business Machines Corporation

    Inventor： Steven Ware Jones ,  Ruchi Asthana ,  Jennifer A. Mallette ,  Jacob Lewis ,  Vivek Salve

    IPC: H04L12/58 ,  G06F40/58 ,  G06F40/47 ,  G06N20/00

    Abstract: For a chat bot, first intent data is provided, including a first instance of sample utterances in a first natural language and intents corresponding to the respective sample utterances. The sample utterances are translated by a computer system to a second natural language as a second instance of the sample utterances. The sample utterances of the second instance are translated by a computer system back to the first natural language as a third instance of the sample utterances. Second intent data is provided including the third instance of the sample utterances and the corresponding intents. An intent classifier of the chat bot is trained to identify respective intents of real time utterances, wherein the identifying is responsive to the intent classifier receiving the real time utterances from a user when the chat bot is in an operating mode and the training includes training the intent classifier on the first and second intent data.

    NATURAL LANGUAGE RESPONSE IMPROVEMENT IN MACHINE ASSISTED AGENTS
    6.
    发明申请
    NATURAL LANGUAGE RESPONSE IMPROVEMENT IN MACHINE ASSISTED AGENTS 有权

    公开(公告)号：US20210026924A1

    公开(公告)日：2021-01-28

    申请号：US16519859

    申请日：2019-07-23

    Applicant: International Business Machines Corporation

    Inventor： Steven Ware Jones ,  Jennifer A. Mallette ,  Arjun Jauhari ,  Vivek Salve

    IPC: G06F17/28 ,  G06F17/27

    Abstract: Using a personal entity analyzer, a personal entity difference between a natural language response to a natural language query and an edited version of the natural language response is scored, the natural language response selected from a set of natural language response recommendations. Using a product entity analyzer, a product entity difference between the natural language response and the edited version of the natural language response is scored. Using a sentence similarity analyzer, a sentence similarity between the natural language response and the edited version of the natural language response is scored. Based on the personal entity difference score, the product entity difference, score and the sentence similarity score, the set of natural language responses is updated. In a natural language interaction, a selected natural language response from the set of natural language responses is outputted.

    ADAPTIVE AUTONOMOUS ROAD SIGN CLASSIFICATION WITH FORERUNNER VEHICLE UTILIZATION
    7.
    发明申请
    ADAPTIVE AUTONOMOUS ROAD SIGN CLASSIFICATION WITH FORERUNNER VEHICLE UTILIZATION 有权

    公开(公告)号：US20250005139A1

    公开(公告)日：2025-01-02

    申请号：US18217461

    申请日：2023-06-30

    Applicant: International Business Machines Corporation

    Inventor： Jana H. Jenkins ,  Jennifer A. Mallette ,  Xin Wang ,  Martin G. Keen

    IPC: G06F21/55

    Abstract: A method for countering adversarial attacks on deep neural networks is disclosed. In one embodiment, such a method includes observing, by a first system, actual traffic behavior within a transportation network. The method classifies, by a deep neural network of a second system, a traffic sign for regulating traffic within the transportation network. The method determines whether a conflict exists between the actual traffic behavior and expected traffic behavior based on the traffic sign. If a conflict is deemed to exist, the method adjusts training data of the deep neural network with respect to classifying the traffic sign. In certain embodiments, the first system includes one or more forerunner vehicles and the second system is an autonomous vehicle. The one or more forerunner vehicles may be configured to travel ahead of the autonomous vehicle when navigating the transportation network. A corresponding system and computer program product are also disclosed.

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