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Patent Agency Ranking
公开(公告)号：US10453455B2
公开(公告)日：2019-10-22
申请号：US15820874
申请日：2017-11-22
Applicant: Adobe Inc.
Inventor： Ramesh Radhakrishna Manuvinakurike , Trung Huu Bui , Walter W. Chang
Abstract: A technique for multiple turn conversational task assistance includes receiving data representing a conversation between a user and an agent. The conversation includes a digitally recorded video portion and a digitally recorded audio portion, where the audio portion corresponds to the video portion. Next, the audio portion is segmented into a plurality of audio chunks. For each of the audio chunks, a transcript of the respective audio chunk is received. Each of the audio chunks is grouped into one or more dialog acts, where each dialog act includes at least one of the respective audio chunks, the validated transcript corresponds to the respective audio chunks, and a portion of the video portion corresponds to the respective audio chunk. Each of the dialog acts is stored in a data corpus.
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公开(公告)号：US20190278844A1
公开(公告)日：2019-09-12
申请号：US15913064
申请日：2018-03-06
Applicant: Adobe Inc.
Inventor： Jacqueline Brixey , Walter W. Chang , Trung Bui , Doo Soon Kim , Ramesh Radhakrishna Manuvinakurike
IPC: G06F17/27 , G06F3/0484 , G06F17/24
Abstract: A framework for annotating image edit requests includes a structure for identifying natural language request as either comments or image edit requests and for identifying the text of a request that maps to an executable action in an image editing program, as well as to identify other entities from the text related to the action. The annotation framework can be used to aid in the creation of artificial intelligence networks that carry out the requested action. An example method includes displaying a test image, displaying a natural language input with selectable text, and providing a plurality of selectable action tag controls and entity tag controls. The method may also include receiving selection of the text, receiving selection of an action tag control for the selected text, generating a labeled pair, and storing the labeled pair with the natural language input as an annotated natural language image edit request.
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公开(公告)号：US10579737B2
公开(公告)日：2020-03-03
申请号：US15913064
申请日：2018-03-06
Applicant: Adobe Inc.
Inventor： Jacqueline Brixey , Walter W. Chang , Trung Bui , Doo Soon Kim , Ramesh Radhakrishna Manuvinakurike
IPC: G06F17/24 , G06F17/27 , G06F17/30 , G06F3/0484
Abstract: A framework for annotating image edit requests includes a structure for identifying natural language request as either comments or image edit requests and for identifying the text of a request that maps to an executable action in an image editing program, as well as to identify other entities from the text related to the action. The annotation framework can be used to aid in the creation of artificial intelligence networks that carry out the requested action. An example method includes displaying a test image, displaying a natural language input with selectable text, and providing a plurality of selectable action tag controls and entity tag controls. The method may also include receiving selection of the text, receiving selection of an action tag control for the selected text, generating a labeled pair, and storing the labeled pair with the natural language input as an annotated natural language image edit request.
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公开(公告)号：US10586528B2
公开(公告)日：2020-03-10
申请号：US15423429
申请日：2017-02-02
Applicant: Adobe Inc.
Abstract: Domain-specific speech recognizer generation with crowd sourcing is described. The domain-specific speech recognizers are generated for voice user interfaces (VUIs) configured to replace or supplement application interfaces. In accordance with the described techniques, the speech recognizers are generated for a respective such application interface and are domain-specific because they are each generated based on language data that corresponds to the respective application interface. This domain-specific language data is used to build a domain-specific language model. The domain-specific language data is also used to collect acoustic data for building an acoustic model. In particular, the domain-specific language data is used to generate user interfaces that prompt crowd-sourcing participants to say selected words represented by the language data for recording. The recordings of these selected words are then used to build the acoustic model. The domain-specific speech recognizers are generated by combining a respective domain-specific language model and crowd-sourced acoustic model.
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公开(公告)号：US20190156822A1
公开(公告)日：2019-05-23
申请号：US15820874
申请日：2017-11-22
Applicant: Adobe Inc.
Inventor： Ramesh Radhakrishna Manuvinakurike , Trung Huu Bui , Walter W. Chang
CPC classification number: G10L15/22 , G06F3/167 , G10L15/04 , G10L15/063 , G10L15/265 , G10L25/57 , G10L25/78 , G10L25/87 , G10L2015/223
Abstract: A technique for multiple turn conversational task assistance includes receiving data representing a conversation between a user and an agent. The conversation includes a digitally recorded video portion and a digitally recorded audio portion, where the audio portion corresponds to the video portion. Next, the audio portion is segmented into a plurality of audio chunks. For each of the audio chunks, a transcript of the respective audio chunk is received. Each of the audio chunks is grouped into one or more dialog acts, where each dialog act includes at least one of the respective audio chunks, the validated transcript corresponds to the respective audio chunks, and a portion of the video portion corresponds to the respective audio chunk. Each of the dialog acts is stored in a data corpus.
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