Cheng Hsiu Wu

US Patent:

7574358, Aug 11, 2009

Filed:

Feb 28, 2005

Appl. No.:

11/067819

Inventors:

Sabine Deligne - New York NY, US
Yuqing Gao - Mount Kisco NY, US
Vaibhava Goel - Elmsford NY, US
Cheng Wu - Mount Kisco NY, US

Assignee:

International Business Machines Corporation - Armonk NY

International Classification:

G10L 15/00

US Classification:

704243, 704246, 704251, 704255, 7042565, 704257

Abstract:

A natural language business system and method is developed to understand the underlying meaning of a person's speech, such as during a transaction with the business system. The system includes a speech recognition engine, and action classification engine, and a control module. The control module causes the system to execute an inventive method wherein the speech recognition and action classification models may be recursively optimized on an unisolated performance metric that is pertinent to the overall performance of the natural language business system, as opposed to the isolated model-specific criteria previously employed.

US Patent:

8571869, Oct 29, 2013

Filed:

May 15, 2008

Appl. No.:

12/121329

Inventors:

Sabine Deligne - New York NY, US
Yuqing Gao - Mount Kisco NY, US
Vaibhava Goel - Elmsford NY, US
Cheng Wu - Mount Kisco NY, US

Assignee:

Nuance Communications, Inc. - Burlington MA

International Classification:

G10L 15/00

US Classification:

704257, 704246, 704247, 704251, 704252

Abstract:

A natural language business system and method is developed to understand the underlying meaning of a person's speech, such as during a transaction with the business system. The system includes a speech recognition engine, and action classification engine, and a control module. The control module causes the system to execute an inventive method wherein the speech recognition and action classification models may be recursively optimized on an unisolated performance metric that is pertinent to the overall performance of the natural language business system, as opposed to the isolated model-specific criteria previously employed.

US Patent:

20070168457, Jul 19, 2007

Filed:

Jan 18, 2006

Appl. No.:

11/334717

Inventors:

Juan Huerta - Bronx NY, US
David Lubensky - Brookfield CT, US
Cheng Wu - Mount Kisco NY, US

Assignee:

International Business Machines Corporation - Armonk NY

International Classification:

G06F 15/16

US Classification:

709217000

Abstract:

Techniques are provided for addressing a problem pertaining to a computer of a user. In an exemplary method, the obtaining of a problem statement associated with the problem pertaining to the computer of the user is facilitated. This can be carried out via speech over a telephony connection. The establishment of a remote access connection between the computer of the user and a remote help desk application can also be facilitated. Furthermore, substantially parallel interaction with the user can be facilitated, via both the telephony connection and the remote access connection to the remote help desk application.

US Patent:

20120209590, Aug 16, 2012

Filed:

Feb 16, 2011

Appl. No.:

13/028555

Inventors:

Juan M. Huerta - Pleasantville NY, US
Cheng Wu - Mount Kisco NY, US

Assignee:

INTERNATIONAL BUSINESS MACHINES CORPORATION - Armonk NY

International Classification:

G06F 17/28

US Classification:

704 7

Abstract:

A method, system, and computer readable storage medium including a computer readable program are provided. The method includes storing a set of sentences in a memory device. The method further includes receiving an input translated phrase and searching the set of sentences for a subset of sentences closest to the input translated phrase based on a set of respective distances to the sentences in the set with respect to the input translated phrase. The method also includes calculating and outputting a language model score for the subset of sentences based on a function of a subset of respective distances pertaining to the subset of sentences.

US Patent:

20130231916, Sep 5, 2013

Filed:

Mar 5, 2012

Appl. No.:

13/412104

Inventors:

Juan M. Huerta - Pleasantville NY, US
David M. Lubensky - Brookfield CT, US
Cheng Wu - Mount Kisco NY, US

Assignee:

INTERNATIONAL BUSINESS MACHINES CORPORATION - Armonk NY

International Classification:

G06F 17/28

US Classification:

704 5

Abstract:

Methods and systems for fast translation memory search include, in response to an input query string, identifying a plurality of hypothesis strings stored in a translation memory as candidates to match the query string. One or more candidates are eliminated, using a processor, where string lengths between the candidates and the query string are at least a cutoff value representing a string edit distance. One or more candidates are eliminated where differences in word frequency distributions between the candidates and the query string are at least the cutoff value. One or more candidates are eliminated by employing a dynamic programming matrix where string edit distances between the candidates and the query string are at least the cutoff value. A number of remaining candidates are outputted as matches to the query string.

US Patent:

20200042642, Feb 6, 2020

Filed:

Aug 2, 2018

Appl. No.:

16/053718

Inventors:

- Armonk NY, US
Song Feng - New York NY, US
Chulaka Gunasekara - Yorktown Heights NY, US
David Nahamoo - Great Neck NY, US
Lazaros Polymenakos - West Harrison NY, US
Sunil D. Shashidhara - White Plains NY, US
Cheng Wu - Bellevue WA, US
Li Zhu - Yorktown Heights NY, US

International Classification:

G06F 17/30
G06N 5/02
G06F 17/27
G06N 3/04
G06N 99/00

Abstract:

A method, apparatus and computer program product for creating a dialog system for web content is described. Knowledge is extracted from a target web application for the dialog system. The knowledge includes an organizational structure of the target web application and domain knowledge pertinent to the target web application. A deep learning process associates the domain knowledge with the organization structure of the target application. A plurality of knowledge sources of different respective types are created from the domain knowledge and the organizational structure. Each of the knowledge sources is used for providing answers to user queries to the dialog system. As part of the invention, a semantic matcher is provided to select among the answers provided by the plurality of knowledge sources for a best answer to a user query.

US Patent:

20200042649, Feb 6, 2020

Filed:

Aug 2, 2018

Appl. No.:

16/053726

Inventors:

- Armonk NY, US
Song Feng - New York NY, US
Chulaka Gunasekara - Yorktown Heights NY, US
David Nahamoo - Great Neck NY, US
Lazaros Polymenakos - West Harrison NY, US
Sunil D. Shashidhara - White Plains NY, US
Cheng Wu - Bellevue WA, US
Li Zhu - Yorktown Heights NY, US

International Classification:

G06F 17/30
G06F 17/27
G06N 5/02
G10L 15/22

Abstract:

A method, apparatus and computer program product for presenting a user interface for a conversational system is described. A user input is received in a dialog between a user and the conversational system, the user input in a natural language. A domain trained semantic matcher is used to determine a set of entities and a user intent from the user input. One or more queries is generated to selected ones of a plurality of knowledge sources, the knowledge sources created from domain specific knowledge. The results from the one or more queries are ranked based on domain specific knowledge. A system response is presented in the dialog based on at least a highest ranked result from the plurality of knowledge sources.

US Patent:

20170192963, Jul 6, 2017

Filed:

Mar 22, 2017

Appl. No.:

15/466531

Inventors:

- Armonk NY, US
Andrzej Sakrajda - Briarcliff Manor NY, US
Hui Wan - White Plains NY, US
Cheng Wu - Mount Kisco NY, US
Sasha P. Caskey - New York NY, US

International Classification:

G06F 17/28

Abstract:

A method of translating information using crowdsourcing includes evaluating a metric related to a content to be translated, determining a priority for the content, queuing the content for the crowdsourcing based on the priority determined from the metric, and translating the information from a language to another language using the crowdsourcing.