Yun Tang

US Patent:

20190303442, Oct 3, 2019

Filed:

Jun 29, 2018

Appl. No.:

16/024475

Inventors:

- Cupertino CA, US
Matthias PAULIK - San Jose CA, US
Yun TANG - Fremont CA, US

International Classification:

G06F 17/28
G10L 15/22
G10L 15/18

Abstract:

Systems and processes for operating an electronic device to train a machine-learning translation system are described. In one process, a first set of training data is obtained. The first set of training data includes at least one payload in a first language and a translation of the at least one payload in a second language. The process further includes obtaining one or more templates for adapting the at least one payload; adapting the at least one payload using the one or more templates to generate at least one adapted payload formulated as a translation request; generating a second set of training data based on the at least one adapted payload; and training the machine-learning translation system using the second set of training data.

US Patent:

20170309029, Oct 26, 2017

Filed:

Oct 28, 2014

Appl. No.:

15/518416

Inventors:

- Houston TX, US
Divya Sharma - Palo Alto CA, US
Jian Fan - San Jose CA, US
Jinman Kang - San Diego CA, US
Yun Tang - San Diego CA, US
Daniel R Tretter - San Jose CA, US

Assignee:

Hewlett-Packard Development Company, L.P. - Houston TX

International Classification:

G06T 7/12
G06T 7/13
G06T 7/11
G06T 7/10
G06T 7/529
G06T 7/194

Abstract:

According to one example for segmenting image data, image data comprising color pixel data, IR data, and depth data is received from a sensor. The image data is segmented into a first list of objects based on at least one computed feature of the image data. At least one object type is determined for at least one object in the first list of objects. The segmentation of the first list of objects is refined into a second list of objects based on the at least one object type. In an example, the second list of objects is output.