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公开(公告)号：US11868444B2
公开(公告)日：2024-01-09
申请号：US17380075
申请日：2021-07-20
CPC分类号： G06F18/40 , G06F18/214 , G06F18/217 , G06N20/00 , G06T19/006 , G06T19/20 , G06V20/20 , G06T2200/24 , G06T2219/2016
摘要： In an approach for creating synthetic visual inspection data sets for training an artificial intelligence computer vision deep learning model utilizing augmented reality, a processor enables a user to capture a plurality of images of an anchor object using a camera on a user computing device. A processor receives the plurality of images of the anchor object from the user. A processor generates a baseline model of an anchor object. A processor generates a training data set. A processor trains the baseline model of the anchor object. A processor creates a trained Artificial Intelligence (AI) computer vision deep learning model. A processor enables the user to interact with the trained AI computer vision deep learning model in an access mode.
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公开(公告)号：US20190121619A1
公开(公告)日：2019-04-25
申请号：US15790158
申请日：2017-10-23
发明人： Blaine H. Dolph , David M. Lubensky , Mal Pattiarachi , Marco Pistoia , Nitendra Rajput , Justin Weisz
IPC分类号： G06F9/44 , G06F3/0484 , G06K9/00
摘要： Techniques are disclosed for identifying which graphical user interface (GUI) screens of an application that is under development would benefit from a voice user interface (VUI). A GUI screen parser analyzes to determine the GUI objects within GUI screens of the application. The parser assigns a speechability score to each analyzed GUI screen. Those GUI screens that have a higher speechability score than a predetermined speechability threshold are indicated as GUI screens that would benefit (e.g., the user experience in interacting with those GUI screens would increase, the number of GUI screens displayed would be reduced, or the like) with the addition of a VUI.
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3.发明授权公开(公告)号：US10565982B2
公开(公告)日：2020-02-18
申请号：US15808169
申请日：2017-11-09
摘要： Techniques for optimizing training data within voice user interface (VUI) of an application under development are disclosed. A VUI feedback module synthesizes human speech of a training phrase. This phrase is presented upon a speaker which is simultaneously captured upon a microphone. A speech to text framework converts the synthesized training phrase into text (textualized training phrase). The VUI feedback module compares the textualized training phrase to the actual training phrase and generates a speech training data structure that identifies similarities or dissimilarities between the textualized training phrase and the actual training phrase. This data structure may be utilized by an application developer computing system to identify training data that is most venerable to misinterpretation when a user interacts with the VUI. The VUI may subsequently be adjusted to account for the vulnerabilities to improve operations or user experience of the VUI.
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4.发明申请公开(公告)号：US20190138270A1
公开(公告)日：2019-05-09
申请号：US15808169
申请日：2017-11-09
摘要： Techniques for optimizing training data within voice user interface (VUI) of an application under development are disclosed. A VUI feedback module synthesizes human speech of a training phrase. This phrase is presented upon a speaker which is simultaneously captured upon a microphone. A speech to text framework converts the synthesized training phrase into text (textualized training phrase). The VUI feedback module compares the textualized training phrase to the actual training phrase and generates a speech training data structure that identifies similarities or dissimilarities between the textualized training phrase and the actual training phrase. This data structure may be utilized by an application developer computing system to identify training data that is most venerable to misinterpretation when a user interacts with the VUI. The VUI may subsequently be adjusted to account for the vulnerabilities to improve operations or user experience of the VUI.
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公开(公告)号：US20230027216A1
公开(公告)日：2023-01-26
申请号：US17380075
申请日：2021-07-20
摘要： In an approach for creating synthetic visual inspection data sets for training an artificial intelligence computer vision deep learning model utilizing augmented reality, a processor enables a user to capture a plurality of images of an anchor object using a camera on a user computing device. A processor receives the plurality of images of the anchor object from the user. A processor generates a baseline model of an anchor object. A processor generates a training data set. A processor trains the baseline model of the anchor object. A processor creates a trained Artificial Intelligence (AI) computer vision deep learning model. A processor enables the user to interact with the trained AI computer vision deep learning model in an access mode.
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公开(公告)号：US10585640B2
公开(公告)日：2020-03-10
申请号：US15790160
申请日：2017-10-23
发明人： Blaine H. Dolph , David M. Lubensky , Mal Pattiarachi , Marco Pistoia , Nitendra Rajput , Justin Weisz
IPC分类号： G06F3/048 , G06F3/16 , G06F17/27 , G06F8/38 , G06F3/0484
摘要： Techniques are disclosed for generating a voice user interface (VUI) modality within an application that includes graphical user interface (GUI) screens. A GUI screen parser analyzes the GUI screens to determine the various navigational GUI screen paths that are associated with edge objects within multiple GUI screens. Some edge objects are identified as select objects or prompt objects. A natural language processing system generates a select object synonym data structure and a prompt object data structure that may be utilized by a VUI generator to generate VUI data structures that give the application VUI modality.
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公开(公告)号：US10481865B2
公开(公告)日：2019-11-19
申请号：US15790162
申请日：2017-10-23
发明人： Blaine H. Dolph , David M. Lubensky , Mal Pattiarachi , Marco Pistoia , Nitendra Rajput , Justin Weisz
摘要： Techniques are disclosed for generating a voice user interface (VUI) modality within an application that includes graphical user interface (GUI) screens. A GUI screen parser analyzes the GUI screens to determine the various navigational GUI screen paths that are associated with edge objects within multiple GUI screens. Some edge objects are identified as select objects or prompt objects. A natural language processing system generates a select object synonym data structure and a prompt object data structure that may be utilized by a VUI generator to generate VUI data structures that give the application VUI modality.
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公开(公告)号：US20190121609A1
公开(公告)日：2019-04-25
申请号：US15790162
申请日：2017-10-23
发明人： Blaine H. Dolph , David M. Lubensky , Mal Pattiarachi , Marco Pistoia , Nitendra Rajput , Justin Weisz
IPC分类号： G06F3/16 , G06F3/0484 , G06F9/44
摘要： Techniques are disclosed for generating a voice user interface (VUI) modality within an application that includes graphical user interface (GUI) screens. A GUI screen parser analyzes the GUI screens to determine the various navigational GUI screen paths that are associated with edge objects within multiple GUI screens. Some edge objects are identified as select objects or prompt objects. A natural language processing system generates a select object synonym data structure and a prompt object data structure that may be utilized by a VUI generator to generate VUI data structures that give the application VUI modality.
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公开(公告)号：US10553203B2
公开(公告)日：2020-02-04
申请号：US15807956
申请日：2017-11-09
摘要： Techniques for optimizing training data within voice user interface (VUI) of an application under development are disclosed. A VUI feedback module synthesizes human speech of a training phrase. This phrase is presented upon a speaker which is simultaneously captured upon a microphone. A speech to text framework converts the synthesized training phrase into text (textualized training phrase). The VUI feedback module compares the textualized training phrase to the actual training phrase and generates a speech training data structure that identifies similarities or dissimilarities between the textualized training phrase and the actual training phrase. This data structure may be utilized by an application developer computing system to identify training data that is most venerable to misinterpretation when a user interacts with the VUI. The VUI may subsequently be adjusted to account for the vulnerabilities to improve operations or user experience of the VUI.
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公开(公告)号：US20190138269A1
公开(公告)日：2019-05-09
申请号：US15807956
申请日：2017-11-09
摘要： Techniques for optimizing training data within voice user interface (VUI) of an application under development are disclosed. A VUI feedback module synthesizes human speech of a training phrase. This phrase is presented upon a speaker which is simultaneously captured upon a microphone. A speech to text framework converts the synthesized training phrase into text (textualized training phrase). The VUI feedback module compares the textualized training phrase to the actual training phrase and generates a speech training data structure that identifies similarities or dissimilarities between the textualized training phrase and the actual training phrase. This data structure may be utilized by an application developer computing system to identify training data that is most venerable to misinterpretation when a user interacts with the VUI. The VUI may subsequently be adjusted to account for the vulnerabilities to improve operations or user experience of the VUI.
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