Abstract: The Abstract of the Disclosure is provided to allow the reader to quickly ascertain the nature of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. In addition, in the foregoing Detailed Description, it can be seen that various features are grouped together in various examples for the purpose of streamlining the disclosure. This method of disclosure is not to be interpreted as reflecting an intention that the claims require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter lies in less than all features of a single disclosed example. Thus, the following claims are hereby incorporated into the Detailed Description, with each claim standing on its own as a separately claimed subject matter.

Abstract: A project management system for a browser application utilizes extracts text from application content loaded into view ports of the browser application and generates a prompt for a generative artificial intelligence (AI) model that includes the extracted text. The model is trained to generate an urgency level classification for the application content based on the extracted text. The project management system receives the urgency level classifications for the application content and causes the tabs of the view ports in which the application content is loaded to be depicted in a manner that is indicative of the urgency level classification of the associated application content.

Abstract: A method for streaming videos with internally-variable frame quality is implemented via a computing system including a processor. The method includes accessing a video including and evenly sampling the video frames. The method includes, for each sampled video frame, analyzing the video frame using a CNN model to determine whether the video frame includes high-relevance region(s). The method also includes, for each sampled video frame including high-relevance region(s), extracting coordinates of the high-relevance region(s) using the CNN model, and for each sampled video frame including high-relevance region(s) and each intervening video frame between the sampled video frame and a next sampled video frame, setting a minimum frame quality for the extracted coordinates.

Abstract: A system and method and for providing speech assistance during a virtual meeting includes receiving a request over a communication network to provide speech assistance during a virtual meeting between a plurality of participants and analyzing speech data of the virtual meeting, via a speech impediment detection engine, to detect a speech impediment for one of the plurality of participants. Upon detecting the speech impediment, an avatar is automatically generated for the participant experiencing speech impediment and the avatar is synchronized with the participant's speech in real-time during the communication session to provide real-time visual feedback to the participant. The avatar is then provided for display to the participant.

Abstract: Methods, systems, and computer storage media for providing context-aware out-of-office (OOO) assistance using an email management engine. Context-aware OOO assistance supports email management operations that provide OOO functionality with artificial intelligence and context-awareness for email management during periods of unavailability. In operation, an email message is accessed. An email message category is determined for the email message. The email message category can be a scheduling meeting category, a requesting information category, or a task delegation category. Based on the email message category, a plurality of OOO operations associated with the email message category are executed. Based on executing the plurality of OOO operations associated with the email message category, a response for the email message is generated. The response is associated with one of the following: scheduling meeting data, requesting information data, or task delegation data.

Abstract: Methods, systems, and computer storage media for providing a disrupted-speech assistance service associated with a disrupted-speech management engine of a meeting management system. The disrupted-speech assistance service is an accessibility service that supports accessibility operations of a disrupted-speech management engine to provide disrupted-speech assistance features in a meeting management system. In operation, meeting data comprising audio data is accessed. The audio data is analyzed to determine that the audio data comprises disrupted-speech at a threshold level of disrupted-speech. Based on the audio data comprising disrupted-speech at the threshold level of disrupted-speech, one or more disrupted-speech assistance operations for a meeting can be executed. The one or more disrupted-speech assistance operations comprises identifying a disrupted-speech word; determining an alternative word for the disrupted-speech word.

Abstract: A system and method and for automatically enhancing an input image includes detecting a genre for the input image using a genre identification machine-learning model and identifying one or more objects in the input image using an object identification machine-learning model. The identified genre and objects are then compared to a list of genre and object tags for images in an image library to identify a plurality of genre and object tags that are similar to the identified genre and objects. A list of edits corresponding to each of the identified similar genre and object tags is then to the input image to generate a plurality of enhanced images for the input image. An aesthetic value is measured for the plurality of enhanced images and at least one of the plurality of enhanced images is provided as a recommendation for enhancing the input image, based on the aesthetic value.

Abstract: An adaptive artificial intelligence (AI) control system receives a prompt for an AI system from a user interface component of a software application on a mobile device. The adaptive AI control system determines a current battery level of the mobile device using a battery level monitoring component. The adaptive AI control system then selects a generative AI model of the AI system to use to generate a response for the prompt based on the current battery level using a model selection component. The generative AI model that is selected is one of a plurality of different generative AI models of the AI system which are capable of processing the prompt, each of the plurality of generative AI models having a different level of complexity.

Abstract: Technology is disclosed herein for the integration of large language model (LLM) services for content analysis in productivity applications. In an implementation, an application identifies content associated with the application executing on the computing apparatus. The application identifies a context relating to the content, wherein the context comprises contextual information by which to evaluate the content. The application generates a prompt for an LLM service which includes the content and the context. The prompt requests an evaluation of the content to recommend supplemental content and submits the prompt to the LLM service. The application receives a response to the prompt from the LLM service which includes a suggestion for supplemental content based on the evaluation and displays, in a user interface of the application, a recommendation based on the suggestion from the LLM service.

Abstract: The Abstract of the Disclosure is provided to allow the reader to quickly ascertain the nature of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. In addition, in the foregoing Detailed Description, it can be seen that various features are grouped together in various examples for the purpose of streamlining the disclosure. This method of disclosure is not to be interpreted as reflecting an intention that the claims require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter lies in less than all features of a single disclosed example. Thus, the following claims are hereby incorporated into the Detailed Description, with each claim standing on its own as a separately claimed subject matter.

Abstract: An inclusive prompt recommendation system for generative AI utilizes an inclusive prompt recommendation model to provide recommendations of inclusive language to include in a prompt in order to promote inclusivity and diversity of generated content. The inclusive prompt recommendation model is trained to analyze input text to identify situations, such as gaming, storytelling, social media, projects or presentations for work/school, and like, where the user's intent is to generate an image or description of a person. The model is trained to identify patterns associated with ways users have historically incorporated inclusive terminology intext. The system can include an ethical filtering mechanism for ensuring that prompt recommendations do not have language that directly or indirectly promotes bias and/or stereotypes.

Abstract: Methods, systems, and computer storage media for providing context-aware out-of-office (OOO) assistance using an email management engine. Context-aware OOO assistance supports email management operations that provide OOO functionality with artificial intelligence and context-awareness for email management during periods of unavailability. In operation, an email message is accessed. An email message category is determined for the email message. The email message category can be a scheduling meeting category, a requesting information category, or a task delegation category. Based on the email message category, a plurality of OOO operations associated with the email message category are executed. Based on executing the plurality of OOO operations associated with the email message category, a response for the email message is generated. The response is associated with one of the following: scheduling meeting data, requesting information data, or task delegation data.

Abstract: A method of and system for providing accessibility for digital ink is carried out by detecting digital ink input on a user interface (UI) screen, the digital ink input being received via a writing instrument used by a user within a given time period; capturing an image of the digital ink input; examining the image of the digital ink input to detect tremors in the user; assigning a level to the tremors based on discontinuities or irregularities in the digital ink input within the given time period; determining based on the level that the digital ink input requires correction; and applying a correction to the digital ink input to correct the digital ink input.

Abstract: A computer readable medium for sizing a product includes instructions, that when executed by at least one processor, cause a computing device to: retrieve from a webpage information on a product including product dimensions; present on a display of a client device a graphical button that upon access by a user activates a camera for capturing an image of an object positioned at a focal distance from the camera, the object having a surface; prompt the user to enter boundary information of an imaginary housing to be placed on the surface; generate the imaginary housing dimensions in two dimensions (2D) based on the boundary information and the focal distance; and determine whether the product fits within the imaginary housing by comparing the product dimensions against the imaginary housing dimensions.

Abstract: A system and method and for providing speech assistance during a virtual meeting includes receiving a request over a communication network to provide speech assistance during a virtual meeting between a plurality of participants and analyzing speech data of the virtual meeting, via a speech impediment detection engine, to detect a speech impediment for one of the plurality of participants. Upon detecting the speech impediment, an avatar is automatically generated for the participant experiencing speech impediment and the avatar is synchronized with the participant's speech in real-time during the communication session to provide real-time visual feedback to the participant. The avatar is then provided for display to the participant.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating and providing pose guides that are tailored to a context of a camera viewfinder stream. In particular, in one or more embodiments, the disclosed systems determine a context of the camera viewfinder stream and provide sample pose images that correspond with the determined context. In response to a selection of a sample pose image, the disclosed systems generate and display a pose guide that is customized to the proportions of a subject depicted in the camera viewfinder stream. The disclosed systems further iteratively modify portions of the generated pose guide to indicate that the subject depicted in the camera viewfinder stream is coming into alignment with the generated pose guide. The disclosed systems automatically capture a digital image when the subject is in total alignment with the generated pose guide.

Abstract: A method for streaming videos with internally-variable frame quality is implemented via a computing system including a processor. The method includes accessing a video including and evenly sampling the video frames. The method includes, for each sampled video frame, analyzing the video frame using a CNN model to determine whether the video frame includes high-relevance region(s). The method also includes, for each sampled video frame including high-relevance region(s), extracting coordinates of the high-relevance region(s) using the CNN model, and for each sampled video frame including high-relevance region(s) and each intervening video frame between the sampled video frame and a next sampled video frame, setting a minimum frame quality for the extracted coordinates.

Abstract: A method for content-aware type-on-path generation is implemented via a computing system including a processor. The method includes surfacing an image via a graphics GUI of a graphics application and detecting one or more salient objects within the image using a CNN model. The method also includes generating a contour map for each detected salient object and generating a path along the contours of each salient object by applying a defined offset to the corresponding contour map. The method further includes applying input text characters as type-on-path along the generated path based at least on user input received via the graphics GUI.

Abstract: Technology is disclosed herein for the integration of large language model (LLM) services for content analysis in productivity applications. In an implementation, an application identifies content associated with the application executing on the computing apparatus. The application identifies a context relating to the content, wherein the context comprises contextual information by which to evaluate the content. The application generates a prompt for an LLM service which includes the content and the context. The prompt requests an evaluation of the content to recommend supplemental content and submits the prompt to the LLM service. The application receives a response to the prompt from the LLM service which includes a suggestion for supplemental content based on the evaluation and displays, in a user interface of the application, a recommendation based on the suggestion from the LLM service.

Abstract: A method for streaming videos with internally-variable frame quality is implemented via a computing system including a processor. The method includes accessing a video including and evenly sampling the video frames. The method includes, for each sampled video frame, analyzing the video frame using a CNN model to determine whether the video frame includes high-relevance region(s). The method also includes, for each sampled video frame including high-relevance region(s), extracting coordinates of the high-relevance region(s) using the CNN model, and for each sampled video frame including high-relevance region(s) and each intervening video frame between the sampled video frame and a next sampled video frame, setting a minimum frame quality for the extracted coordinates.