公开(公告)号：US20180293221A1

公开(公告)日：2018-10-11

申请号：US16005470

申请日：2018-06-11

Applicant: Microsoft Technology Licensing, LLC

Inventor： Erich-Soren FINKELSTEIN ,  Han Yee Mimi FUNG ,  Aleksandar UZELAC ,  Oz SOLOMON ,  Keith Coleman HEROLD ,  Vivek PRADEEP ,  Zongyi LIU ,  Kazuhito KOISHIDA ,  Haithem ALBADAWI ,  Steven Nabil BATHICHE ,  Christopher Lance NUESMEYER ,  Michelle Lynn HOLTMANN ,  Christopher Brian QUIRK ,  Pablo Luis SALA

IPC: G06F17/27 ,  G10L17/00 ,  G10L15/22 ,  G06F15/18

Abstract: A method to execute computer-actionable directives conveyed in human speech comprises: receiving audio data recording speech from one or more speakers; converting the audio data into a linguistic representation of the recorded speech; detecting a target corresponding to the linguistic representation; committing to the data structure language data associated with the detected target and based on the linguistic representation; parsing the data structure to identify one or more of the computer-actionable directives; and submitting the one or more of the computer-actionable directives to the computer for processing.

公开(公告)号：US20180233145A1

公开(公告)日：2018-08-16

申请号：US15832672

申请日：2017-12-05

Applicant: Microsoft Technology Licensing, LLC

Inventor： Steven Nabil BATHICHE ,  Flavio Protasio RIBEIRO ,  Vivek PRADEEP

IPC: G10L15/22 ,  H04R1/40 ,  H04R3/00 ,  G10L15/18 ,  G10L15/28 ,  G01S5/18 ,  G06T7/60 ,  G06T7/73 ,  G06T7/246

Abstract: A first intelligent assistant computing device configured to receive and respond to natural language inputs provided by human users syncs to a reference clock of a wireless computer network. The first intelligent assistant computing device receives a communication sent by a second intelligent assistant computing device indicating a signal emission time at which the second intelligent assistant computing device emitted a position calibration signal. The first intelligent assistant computing device records a signal detection time at which the position calibration signal was detected. Based on a difference between 1) the signal emission time and the signal detection time, and 2) a known propagation speed of the position calibration signal, a distance between the first and second intelligent assistant computing devices is calculated.

公开(公告)号：US20250053748A1

公开(公告)日：2025-02-13

申请号：US18232485

申请日：2023-08-10

Applicant: Microsoft Technology Licensing, LLC

Inventor： Mohsen FAYYAZ ,  Eric Chris Wolfgang SOMMERLADE ,  Justin James WAGLE ,  Vivek PRADEEP

IPC: G06F40/35 ,  G06F40/284 ,  G06N20/00

Abstract: A technique uses a machine-trained model to generate a response based on a prompt which expresses current input information and abstract token information. The abstract token information summarizes a full dialogue history of a dialogue, and is generated by the model itself. The technique reduces the size of the prompt by incorporating the abstract summary information in lieu of the full dialogue history. A training system trains the machine-trained model by successively improving the predictive accuracy of the machine-trained model, while rewarding the machine-trained model based on an extent to which the machine-trained model compresses instances of abstract token information.

公开(公告)号：US20250005072A1

公开(公告)日：2025-01-02

申请号：US18216366

申请日：2023-06-29

Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC

Inventor： Elizabeth Picchietti SALOWITZ ,  David Ben PERRY ,  Carlos A.C. PESSOA ,  Vivek PRADEEP ,  Sharath VISWANATHAN ,  Nathan James LUQUETTA-FISH ,  Steven BATHICHE ,  Eric Chris Wolfgang SOMMERLADE ,  Jose Antonio LARA SILVA

IPC: G06F16/44 ,  G06F16/438

Abstract: Machine learning techniques are leveraged to provide personalized assistance on a computing device. In some configurations a timeline of a user's interactions with the computing device is generated. For example, screenshots and audio streams may be saved as entries in the timeline. Context—the state of the computing device when the entry is created, such as which documents and websites are open—is also stored. Entries in the timeline are processed by a model to generate embedding vectors. The timeline may be searched by finding the embedding vector that is closest to an embedding vector derived from a search query. The user may select a query result, causing the associated context to be restored. For example, if the query is “show me all documents related to my upcoming trip to Japan”, the query result may open documents and websites that were open when booking a flight to Japan.

公开(公告)号：US20240104103A1

公开(公告)日：2024-03-28

申请号：US17953048

申请日：2022-09-26

Applicant: Microsoft Technology Licensing, LLC

Inventor： Eric Chris Wolfgang SOMMERLADE ,  Vivek PRADEEP ,  Steven N. BATHICHE ,  Nathan LUQUETTA-FISH

IPC: G06F16/2457 ,  G06F16/22 ,  G06F40/30

CPC classification number: G06F16/24575 ,  G06F16/2228 ,  G06F40/30

Abstract: Methods and systems for generating and using a semantic index are provided. In some examples, content data is received. The content data includes a plurality of subsets of content data. Each of the plurality of subsets of content data are labelled, based on a semantic context corresponding to the content data. The plurality of subsets of content data and their corresponding labels are stored. The plurality of subsets of content data are grouped, based on their labels, thereby generating one or more groups of subsets of content data. Further, a computing device is adapted to perform an action, based on the one or more groups of subsets of content data.

公开(公告)号：US20220122235A1

公开(公告)日：2022-04-21

申请号：US17073256

申请日：2020-10-16

Applicant: Microsoft Technology Licensing, LLC

Inventor： Luming LIANG ,  Ilya Dmitriyevich ZHARKOV ,  Vivek PRADEEP ,  Faezeh AMJADI

IPC: G06T5/00 ,  G06T5/50 ,  G06T3/40 ,  G06N3/08 ,  G06N3/04

Abstract: A computational photography system is described herein including a guidance system and a detail enhancement system. The guidance system uses a first neural network that maps an original image provided by an image sensor to a guidance image, which represents a color-corrected and lighting-corrected version of the original image. A combination unit combines the original image and the guidance image to produce a combined image. A detail-enhancement system then uses a second neural network to map the combined image to a predicted image. The predicted image supplements the guidance provided by the first neural network by sharpening details in the original image. A training system is also described herein for training the first and second neural networks. The training system alternates in the data it feeds the second neural network, first using a guidance image as input to the second neural network, and then using a corresponding ground-truth image.