Peking University, B.S., 2002; University of Memphis, Ph.D., 2009; University of Tennessee, Health Science Center and University of Memphis (joint program), M.S., 2004
Law School:
Santa Clara University School of Law, J.D., 2018
Name / Title
Company / Classification
Phones & Addresses
Jing Zheng
Skyline Information Technologies Computers Software & Services
114 Perimeter Rd, Unit C, Nashua, NH 03063-1335 (603)8834188
Jing Zheng Principal
Star T Construction Single-Family House Construction
2840 Eastman Ave, Oakland, CA 94619 (510)5060997
Jing Ye Zheng President
Great Wall Iron Works, Inc Structural Steel Erection
2868 E7 St, Oakland, CA 94601 2868 E 7 St, Oakland, CA 94601
License Records
Jing Zheng
License #:
239026652 - Active
Issued Date:
Nov 21, 2011
Expiration Date:
Sep 30, 2018
Type:
Registered Certified Public Accountant
Jing Zheng
License #:
CC-0004472 - Active
Category:
Accountancy
Issued Date:
Nov 20, 2003
Type:
C.P.A. Certificate
Us Patents
Method Of Dynamically Altering Grammars In A Memory Efficient Speech Recognition System
John W. Butzberger - Menlo Park CA, US Horacio E. Franco - Menlo Park CA, US Leonardo Neumeyer - Palo Alto CA, US Jing Zheng - Redwood city CA, US
Assignee:
SRI International - Menlo Park CA
International Classification:
G10L 15/18
US Classification:
7042701, 704257
Abstract:
A method of speech recognition that uses hierarchical data structures that include a top level grammar and various related subgrammars, such as word, phone, and state subgrammars. A speech signal is acquired, and a probabilistic search is performed using the speech signal as an input, and using the (unexpanded) grammars and subgrammars as possible inputs. Memory is allocated to a subgrammar when a transition to that subgrammar is made during the probabilistic search. The subgrammar may then be expanded and evaluated, and the probability of a match between the speech signal and an element of the subgrammar for which memory has been allocated may be computed. Because unexpanded grammars and subgrammars take up very little memory, this method enables systems to recognize and process a larger vocabulary that would otherwise be possible. This method also permits grammars and subgrammars to be added, deleted, or selected by a remote computer while the speech recognition system is operating, allowing speech recognition systems to have a nearly unlimited vocabulary.
Method And Apparatus For Obtaining Complete Speech Signals For Speech Recognition Applications
Victor Abrash - Montara CA, US Federico Cesari - Menlo Park CA, US Horacio Franco - Menlo Park CA, US Christopher George - Los Osos CA, US Jing Zheng - Sunnyvale CA, US
Assignee:
SRI International - Menlo Park CA
International Classification:
G10L 15/14
US Classification:
704233, 704275
Abstract:
The present invention relates to a method and apparatus for obtaining complete speech signals for speech recognition applications. In one embodiment, the method continuously records an audio stream comprising a sequence of frames to a circular buffer. When a user command to commence or terminate speech recognition is received, the method obtains a number of frames of the audio stream occurring before or after the user command in order to identify an augmented audio signal for speech recognition processing. In further embodiments, the method analyzes the augmented audio signal in order to locate starting and ending speech endpoints that bound at least a portion of speech to be processed for recognition. At least one of the speech endpoints is located using a Hidden Markov Model.
Method And Apparatus For Error Correction In Speech Recognition Applications
Horacio Franco - Menlo Park CA, US Gregory Myers - San Francisco CA, US Jing Zheng - Sunnyvale CA, US Federico Cesari - Menlo Park CA, US Cregg Cowan - Mountain View CA, US
Assignee:
SRI International - Menlo Park CA
International Classification:
G10L 15/22
US Classification:
704255
Abstract:
In one embodiment, the present invention is a method and apparatus for error correction in speech recognition applications. In one embodiment, a method for recognizing user speech includes receiving a first utterance from the user, receiving a subsequent utterance from the user, and combining acoustic evidence from the first utterance with acoustic evidence from the subsequent utterance in order to recognize the first utterance. It is assumed that, if the first utterance has been incorrectly recognized on a first attempt, the user will repeat the first utterance (or at least the incorrectly recognized portion of the first utterance) in the subsequent utterance.
Method And Apparatus For Adding New Vocabulary To Interactive Translation And Dialogue Systems
KRISTIN PRECODA - Mountain View CA, US HORACIO FRANCO - Menlo Park CA, US JING ZHENG - Sunnyvale CA, US MICHAEL FRANDSEN - Helena MT, US VICTOR ABRASH - Montara CA, US MURAT AKBACAK - Palo Alto CA, US ANDREAS STOLCKE - Berkeley CA, US
International Classification:
G06F 17/28
US Classification:
704 2, 704E11001
Abstract:
The present invention relates to a method and apparatus for adding new vocabulary to interactive translation and dialogue systems. In one embodiment, a method for adding a new word to a vocabulary of an interactive dialogue includes receiving an input signal that includes at least one word not currently in the vocabulary, inserting the word into a dynamic component of a search graph associated with the vocabulary, and compiling the dynamic component independently of a permanent component of the search graph to produce a new sub-grammar, where the permanent component comprises a plurality of words that are permanently part of the search graph.
Method And Apparatus For Computing Gaussian Likelihoods
XIN LEI - SUNNYVALE CA, US JING ZHENG - SAN JOSE CA, US
International Classification:
G10L 15/14
US Classification:
7042561, 704E15034
Abstract:
The present invention relates to a method and apparatus for computing Gaussian likelihoods. One embodiment of a method for processing a speech sample includes generating a feature vector for each frame of the speech signal, evaluating the feature vector in accordance with a hierarchical Gaussian shortlist, and producing a hypothesis regarding a content of the speech signal, based on the evaluating.
Method And Apparatus For Adapting A Language Model In Response To Error Correction
The present invention relates to a method and apparatus for adapting a language model in response to error correction. One embodiment of a method for processing an input signal including human language includes receiving the input signal and applying a statistical language model combined with a separate, corrective language model to the input signal in order to produce a processing result.
Generating And Utilizing A Digital Knowledge Graph To Provide Contextual Recommendations In Digital Content Editing Applications
- San Jose CA, US Manasi Deshmukh - San Francisco CA, US Ming Liu - Sunnyvale CA, US Ashok Gupta - San Jose CA, US Karthik Suresh - San Jose CA, US Chirag Arora - San Jose CA, US Jing Zheng - San Jose CA, US Ravindra Sadaphule - San Jose CA, US Vipul Dalal - Cupertino CA, US Andrei Stefan - San Francisco CA, US
International Classification:
G06F 9/451 G06T 11/60 G06N 5/02 G06F 40/20
Abstract:
This disclosure describes methods, non-transitory computer readable storage media, and systems that generate a digital knowledge graph based on a plurality of tutorial content items to generate recommendations of digital resource items. Specifically, the disclosed system extracts a plurality of tasks, subject categories related to the tasks, and context signals related to an environment for the tasks from a plurality of tutorial content items for one or more digital content editing applications. The disclosed system generates a digital knowledge graph including nodes corresponding to the tasks and subject categories connected via edges based on relationships extracted from the tutorial content items. In some embodiments, the disclosed system also includes nodes corresponding to digital resource items in the digital knowledge graph or in a subgraph. The disclosed system utilizes the digital knowledge graph with context data to provide a recommendation of digital resource items for display at a client device.
- Redwood Shores CA, US Giridhar Ravipati - Foster City CA, US Ian Neall - Henley-on-Thames, GB Frank Lange - Woerden, NL Jing Zheng - Foster City CA, US Mahesh Girkar - Los Altos CA, US David Gagne - Goffstown NH, US Nitin Karkhanis - Nashua NH, US Sadhana Kyathappala - Westford MA, US Qingguang Cui - Redwood Shores CA, US
International Classification:
G06F 16/27 G06F 16/23 G06F 11/14
Abstract:
Herein is high availability for online transaction processing with redundancy and redo for a federation of pluggable databases and container databases. In an embodiment of a federation of container database management systems that includes a first container database, first redo data of a first pluggable database in a second container database is obtained based on a database dictionary in the first container database. To the first pluggable database in the first container database, the first redo data of the first pluggable database in the second container database is applied. Based on the database dictionary in the first container database, second redo data of a second pluggable database in a third container database is obtained. To the second pluggable database in the first container database, without modifying content of the first pluggable database in the first container database, the second redo data of the second pluggable database in the third container database is applied.