Patents by Inventor Kai-Fu Lee

Kai-Fu Lee has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 10826320
    Abstract: A solar power system may comprise a solar panel set, a controller, a lithium battery set, and at least a DC load. The controller has a control unit built therein to control a double-contact relay, a single-contact relay, and a transformer. The rated voltage of the solar panel set is higher than the rated voltage of the lithium battery set between 115% and 130%. When the actual voltage of the solar panel set is lower than 115% of the rated voltage of the lithium battery set, the solar panel set is configured to low-loss charge the lithium battery set under the low illumination condition. When the actual voltage of the solar panel set is higher than 115% of the rated voltage of the lithium battery set, the solar panel set under the high illumination condition is adapted to have voltage-drop through the transformer and high-efficiently charge the lithium battery set.
    Type: Grant
    Filed: February 11, 2019
    Date of Patent: November 3, 2020
    Inventors: Austin Lai, Kai-Yang Cheng, Wei-Fu Hsu, Kuan-Ching Lee, Hui-Ping Yang
  • Publication number: 20200259362
    Abstract: A solar power system may comprise a solar panel set, a controller, a lithium battery set, and at least a DC load. The controller has a control unit built therein to control a double-contact relay, a single-contact relay, and a transformer. The rated voltage of the solar panel set is higher than the rated voltage of the lithium battery set between 115% and 130%. When the actual voltage of the solar panel set is lower than 115% of the rated voltage of the lithium battery set, the solar panel set is configured to low-loss charge the lithium battery set under the low illumination condition. When the actual voltage of the solar panel set is higher than 115% of the rated voltage of the lithium battery set, the solar panel set under the high illumination condition is adapted to have voltage-drop through the transformer and high-efficiently charge the lithium battery set.
    Type: Application
    Filed: February 11, 2019
    Publication date: August 13, 2020
    Applicant: AVERTRONICS INC.
    Inventors: Austin Lai, Kai-Yang Cheng, Wei-Fu Hsu, Kuan-Ching Lee, Hui-Ping Yang
  • Patent number: 10327629
    Abstract: An oral dilator includes a first body, a second body, a rotary member, and a positioning member. The first body includes a housing and a first duckbilled element. The second body includes a second duckbilled element corresponding to the first duckbilled element. The rotary member drives the second body to rotate. The positioning member is on the first body and selectively locks or unlocks the relative position between the first duckbilled element and the second duckbilled element when the second duckbilled element is driven to rotate by the rotary member.
    Type: Grant
    Filed: March 22, 2017
    Date of Patent: June 25, 2019
    Assignees: MEGAFORCE COMPANY LIMITED, MACKAY MEMORIAL HOSPITAL
    Inventors: Pei-Yi Lee, Shu-Fen Chen, Tien-Fu Chen, Kai-Ping Wang, Shunfeng Huang, Yi-Shun Chung, Shu-Hui Huang, Yu-Siang Ji, Zhen Wei Wu
  • Patent number: 7424675
    Abstract: A language input architecture converts input strings of phonetic text to an output string of language text. The language input architecture has a search engine, one or more typing models, a language model, and one or more lexicons for different languages. The typing model is configured to generate a list of probable typing candidates that may be substituted for the input string based on probabilities of how likely each of the candidate strings was incorrectly entered as the input string. The language model provides probable conversion strings for each of the typing candidates based on probabilities of how likely a probable conversion output string represents the candidate string. The search engine combines the probabilities of the typing and language models to find the most probable conversion string that represents a converted form of the input string.
    Type: Grant
    Filed: September 27, 2004
    Date of Patent: September 9, 2008
    Assignee: Microsoft Corporation
    Inventors: Kai-Fu Lee, Zheng Chen, Jian Han
  • Patent number: 7403888
    Abstract: A language input architecture receives input text (e.g., phonetic text of a character-based language) entered by a user from an input device (e.g., keyboard, voice recognition). The input text is converted to an output text (e.g., written language text of a character-based language). The language input architecture has a user interface that displays the output text and unconverted input text in line with one another. As the input text is converted, it is replaced in the UI with the converted output text. In addition to this in-line input feature, the UI enables in-place editing or error correction without requiring the user to switch modes from an entry mode to an edit mode. To assist with this in-place editing, the UI presents pop-up windows containing the phonetic text from which the output text was converted as well as first and second candidate lists that contain small and large sets of alternative candidates that might be used to replace the current output text.
    Type: Grant
    Filed: June 28, 2000
    Date of Patent: July 22, 2008
    Assignee: Microsoft Corporation
    Inventors: Jian Wang, Gao Zhang, Jian Han, Zheng Chen, Xianoning Ling, Kai-Fu Lee
  • Patent number: 7302640
    Abstract: A language input architecture converts input strings of phonetic text to an output string of language text. The language input architecture has a search engine, typing models, a language model, and one or more lexicons for different languages. Each typing model is trained on real data, and learns probabilities of typing errors. The typing model is configured to generate a list of probable typing candidates that may be substituted for the input string based on probabilities of how likely each of the candidate strings was incorrectly entered as the input string. The language model provides probable conversion strings for each of the typing candidates based on probabilities of how likely a probable conversion output string represents the candidate string. The search engine combines the probabilities of the typing and language models to find the most probable conversion string that represents a converted form of the input string.
    Type: Grant
    Filed: October 21, 2004
    Date of Patent: November 27, 2007
    Assignee: Microsoft Corporation
    Inventors: Kai-Fu Lee, Zheng Chen, Jian Han
  • Patent number: 7275029
    Abstract: A method for the joint optimization of language model performance and size is presented comprising developing a language model from a tuning set of information, segmenting at least a subset of a received textual corpus and calculating a perplexity value for each segment and refining the language model with one or more segments of the received corpus based, at least in part, on the calculated perplexity value for the one or more segments.
    Type: Grant
    Filed: June 30, 2000
    Date of Patent: September 25, 2007
    Assignee: Microsoft Corporation
    Inventors: Jianfeng Gao, Kai-Fu Lee, Mingjing Li, Hai-Feng Wang, Dong-Feng Cai, Lee-Feng Chien
  • Patent number: 7216066
    Abstract: A method is presented comprising assigning each of a plurality of segments comprising a received corpus to a node in a data structure denoting dependencies between nodes, and calculating a transitional probability between each of the nodes in the data structure.
    Type: Grant
    Filed: February 22, 2006
    Date of Patent: May 8, 2007
    Assignee: Microsoft Corporation
    Inventors: Shuo Di, Kai-Fu Lee, Lee-Feng Chien, Zheng Chen, Jianfeng Gao
  • Patent number: 7165019
    Abstract: A language input architecture converts input strings of phonetic text (e.g., Chinese Pinyin) to an output string of language text (e.g., Chinese Hanzi) in a manner that minimizes typographical errors and conversion errors that occur during conversion from the phonetic text to the language text. The language input architecture has a search engine, one or more typing models, a language model, and one or more lexicons for different languages. Each typing model is trained on real data, and learns probabilities of typing errors. The typing model is configured to generate a list of probable typing candidates that may be substituted for the input string based on probabilities of how likely each of the candidate strings was incorrectly entered as the input string.
    Type: Grant
    Filed: June 28, 2000
    Date of Patent: January 16, 2007
    Assignee: Microsoft Corporation
    Inventors: Kai-Fu Lee, Zheng Chen, Jian Han
  • Publication number: 20060184341
    Abstract: A method is presented comprising assigning each of a plurality of segments comprising a received corpus to a node in a data structure denoting dependencies between nodes, and calculating a transitional probability between each of the nodes in the data structure.
    Type: Application
    Filed: February 22, 2006
    Publication date: August 17, 2006
    Applicant: Microsoft Corporation
    Inventors: Shuo Di, Kai-Fu Lee, Lee-Feng Chien, Zheng Chen, Jianfeng Gao
  • Patent number: 7020587
    Abstract: The generation and management of a language model data structure include assigning each segment of a received corpus to a node in a data structure that denotes dependencies between the respective nodes. A transitional probability between each of the nodes in the data structure is calculated. A frequency of occurrence is calculated for each item of the respective segments, and those nodes of the data structure associated with items that do not meet a minimum frequency of occurrence threshold are removed. The data structure may be managed across a system memory of a computer system and an extended memory of the computer system.
    Type: Grant
    Filed: June 30, 2000
    Date of Patent: March 28, 2006
    Assignee: Microsoft Corporation
    Inventors: Shuo Di, Kai-Fu Lee, Lee-Feng Chien, Zheng Chen, Jianfeng Gao
  • Patent number: 6904402
    Abstract: A method for optimizing a language model is presented comprising developing an initial language model from a lexicon and segmentation derived from a received corpus using a maximum match technique, and iteratively refining the initial language model by dynamically updating the lexicon and re-segmenting the corpus according to statistical principles until a threshold of predictive capability is achieved.
    Type: Grant
    Filed: June 30, 2000
    Date of Patent: June 7, 2005
    Assignee: Microsoft Corporation
    Inventors: Hai-Feng Wang, Chang-Ning Huang, Kai-Fu Lee, Shuo Di, Jianfeng Gao, Dong-Feng Cai, Lee-Feng Chien
  • Publication number: 20050086590
    Abstract: A language input architecture converts input strings of phonetic text (e.g., Chinese Pinyin) to an output string of language text (e.g., Chinese Hanzi) in a manner that minimizes typographical errors and conversion errors that occur during conversion from the phonetic text to the language text. The language input architecture has a search engine, one or more typing models, a language model, and one or more lexicons for different languages. Each typing model is trained on real data, and learns probabilities of typing errors. The typing model is configured to generate a list of probable typing candidates that may be substituted for the input string based on probabilities of how likely each of the candidate strings was incorrectly entered as the input string. The probable typing candidates may be stored in a database. The language model provides probable conversion strings for each of the typing candidates based on probabilities of how likely a probable conversion output string represents the candidate string.
    Type: Application
    Filed: October 21, 2004
    Publication date: April 21, 2005
    Applicant: Microsoft Corporation
    Inventors: Kai-Fu Lee, Zheng Chen, Jian Han
  • Publication number: 20050060138
    Abstract: A language input architecture receives input text (e.g., phonetic text of a character-based language) entered by a user from an input device (e.g., keyboard, voice recognition). The input text is converted to an output text (e.g., written language text of a character-based language). The language input architecture has a user interface that displays the output text and unconverted input text in line with one another. As the input text is converted, it is replaced in the UI with the converted output text. In addition to this in-line input feature, the UI enables in-place editing or error correction without requiring the user to switch modes from an entry mode to an edit mode. To assist with this in-place editing, the UI presents pop-up windows containing the phonetic text from which the output text was converted as well as first and second candidate lists that contain small and large sets of alternative candidates that might be used to replace the current output text.
    Type: Application
    Filed: July 23, 2004
    Publication date: March 17, 2005
    Applicant: Microsoft Corporation
    Inventors: Jian Wang, Gao Zhang, Jian Han, Zheng Chen, Xianoning Ling, Kai-Fu Lee
  • Publication number: 20050044495
    Abstract: A language input architecture converts input strings of phonetic text to an output string of language text. The language input architecture has a search engine, one or more typing models, a language model, and one or more lexicons for different languages. The typing model is configured to generate a list of probable typing candidates that may be substituted for the input string based on probabilities of how likely each of the candidate strings was incorrectly entered as the input string. The language model provides probable conversion strings for each of the typing candidates based on probabilities of how likely a probable conversion output string represents the candidate string. The search engine combines the probabilities of the typing and language models to find the most probable conversion string that represents a converted form of the input string.
    Type: Application
    Filed: September 27, 2004
    Publication date: February 24, 2005
    Applicant: Microsoft Corporation
    Inventors: Kai-Fu Lee, Zheng Chen, Jian Han
  • Patent number: 6848080
    Abstract: A language input architecture converts input strings of phonetic text to an output string of language text. The language input architecture has a search engine, one or more typing models, a language model, and one or more lexicons for different languages. The typing model is configured to generate a list of probable typing candidates that may be substituted for the input string based on probabilities of how likely each of the candidate strings was incorrectly entered as the input string. The language model provides probable conversion strings for each of the typing candidates based on probabilities of how likely a probable conversion output string represents the candidate string. The search engine combines the probabilities of the typing and language models to find the most probable conversion string that represents a converted form of the input string.
    Type: Grant
    Filed: June 28, 2000
    Date of Patent: January 25, 2005
    Assignee: Microsoft Corporation
    Inventors: Kai-Fu Lee, Zheng Chen, Jian Han
  • Publication number: 20040243568
    Abstract: A search engine architecture is designed to handle a full range of user queries, from complex sentence-based queries to simple keyword searches. The search engine architecture includes a natural language parser that parses a user query and extracts syntactic and semantic information. The parser is robust in the sense that it not only returns fully-parsed results (e.g., a parse tree), but is also capable of returning partially-parsed fragments in those cases where more accurate or descriptive information in the user query is unavailable. A question matcher is employed to match the fully-parsed output and the partially-parsed fragments to a set of frequently asked questions (FAQs) stored in a database. The question matcher then correlates the questions with a group of possible answers arranged in standard templates that represent possible solutions to the user query. The search engine architecture also has a keyword searcher to locate other possible answers by searching on any keywords returned from the parser.
    Type: Application
    Filed: March 22, 2004
    Publication date: December 2, 2004
    Inventors: Hai-Feng Wang, Kai-Fu Lee, Qiang Yang
  • Publication number: 20040210434
    Abstract: A method for optimizing a language model is presented comprising developing an initial language model from a lexicon and segmentation derived from a received corpus using a maximum match technique, and iteratively refining the initial language model by dynamically updating the lexicon and re-segmenting the corpus according to statistical principles until a threshold of predictive capability is achieved.
    Type: Application
    Filed: May 10, 2004
    Publication date: October 21, 2004
    Applicant: Microsoft Corporation
    Inventors: Hai-Feng Wang, Chang-Ning Huang, Kai-Fu Lee, Shuo Di, Jianfeng Gao, Dong-Feng Cai, Lee-Feng Chien
  • Patent number: 6766320
    Abstract: A search engine architecture is designed to handle a full range of user queries, from complex sentence-based queries to simple keyword searches. The search engine architecture includes a natural language parser that parses a user query and extracts syntactic and semantic information. The parser is robust in the sense that it not only returns fully-parsed results (e.g., a parse tree), but is also capable of returning partially-parsed fragments in those cases where more accurate or descriptive information in the user query is unavailable. A question matcher is employed to match the fully-parsed output and the partially-parsed fragments to a set of frequently asked questions (FAQs) stored in a database. The question matcher then correlates the questions with a group of possible answers arranged in standard templates that represent possible solutions to the user query. The search engine architecture also has a keyword searcher to locate other possible answers by searching on any keywords returned from the parser.
    Type: Grant
    Filed: August 24, 2000
    Date of Patent: July 20, 2004
    Assignee: Microsoft Corporation
    Inventors: Hai-Feng Wang, Kai-Fu Lee, Qiang Yang
  • Patent number: 5757964
    Abstract: A system for automatic subcharacter unit and lexicon generation for handwriting recognition comprises a processing unit, a handwriting input device, and a memory wherein a segmentation unit, a subcharacter generation unit, a lexicon unit, and a modeling unit reside. The segmentation unit generates feature vectors corresponding to sample characters. The subcharacter generation unit clusters feature vectors and assigns each feature vector associated with a given cluster an identical label. The lexicon unit constructs a lexical graph for each character in a character set. The modeling unit generates a Hidden Markov Model for each set of identically-labeled feature vectors. After a first set of lexical graphs and Hidden Markov Models have been created, the subcharacter generation unit determines for each feature vector which Hidden Markov Model produces a highest likelihood value.
    Type: Grant
    Filed: July 29, 1997
    Date of Patent: May 26, 1998
    Assignee: Apple Computer, Inc.
    Inventors: Kai-Fu Lee, Yen-Lu Chow, Kamil Grajski