Patents by Inventor Kyosuke NISHIDA

Kyosuke NISHIDA 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: 12112275
    Abstract: There is provided a learning device for learning a neural network used for search of external knowledge in order to increase search accuracy of external knowledge required for arithmetic processing. With an input sentence Q as an input, an external knowledge search unit 22 selects pieces of external knowledge based on similarity degrees between pieces of external knowledge included in an external knowledge database 2 and the input sentence Q, using a neural network, and causes the selected pieces of external knowledge to be search results R2. A processing unit 14 acquires a response sentence A to the input sentence Q by arithmetic processing with the input sentence Q and the selected pieces of external knowledge as an input. A consideration calculation unit 23 calculates a consideration v determined from an index indicating correctness of the response sentence A based on a true output T given to the input sentence Q in advance and an index indicating quality of the selected pieces of external knowledge.
    Type: Grant
    Filed: November 8, 2019
    Date of Patent: October 8, 2024
    Assignee: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
    Inventors: Kosuke Nishida, Kyosuke Nishida, Hisako Asano, Junji Tomita
  • Publication number: 20240320440
    Abstract: A generation unit that takes a question Qi that is a word sequence representing a current question in a dialogue, a document P used to generate an answer Ai to the question Qi, a question history {Qi-1, . . . , Qi-k} that is a set of word sequences representing k past questions, and an answer history {Ai-1, . . . , Ai-k} that is a set of word sequences representing answers to the k questions as inputs, and generates the answer Ai by machine reading comprehension in an extractive mode or a generative mode using pre-trained model parameters is provided.
    Type: Application
    Filed: May 22, 2024
    Publication date: September 26, 2024
    Applicant: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
    Inventors: Yasuhito OSUGI, Itsumi SAITO, Kyosuke NISHIDA, Hisako ASANO, Junji TOMITA
  • Publication number: 20240321011
    Abstract: A nonverbal information generation apparatus includes a nonverbal information generation unit that generates time-information-stamped nonverbal information that corresponds to time-information-stamped text feature quantities on the basis of the time-information-stamped text feature quantities and a learned nonverbal information generation model. The time-information-stamped text feature quantities are configured to include feature quantities that have been extracted from text and time information representing times assigned to predetermined units of the text. The nonverbal information is information for controlling an expression unit that expresses behavior that corresponds to the text.
    Type: Application
    Filed: April 10, 2024
    Publication date: September 26, 2024
    Applicant: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
    Inventors: Ryo ISHII, Ryuichiro Higashinaka, Taichi Katayama, Junji Tomita, Nozomi Kobayashi, Kyosuke Nishida
  • Patent number: 12056168
    Abstract: A learning apparatus according to an embodiment has a feature generation means configured to take a search query, a first document related to the search query, and a second document that is not related to the search query as input, and generate a feature of the search query, a feature of the first document, and a feature of the second document, by using model parameters of a neural network, and an update means configured to take the feature of the search query, the feature of the first document, and the feature of the second document as input, and update the model parameters by using an error function including a cost function that is a differentiable approximation function of an L0 norm.
    Type: Grant
    Filed: January 29, 2020
    Date of Patent: August 6, 2024
    Assignee: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
    Inventors: Taku Hasegawa, Kyosuke Nishida, Junji Tomita, Hisako Asano
  • Patent number: 12026472
    Abstract: A generation unit that takes a question Qi that is a word sequence representing a current question in a dialogue, a document P used to generate an answer Ai to the question Qi, a question history {Qi-1, . . . , Qi-k} that is a set of word sequences representing k past questions, and an answer history {Ai-1, . . . , Ai-k} that is a set of word sequences representing answers to the k questions as inputs, and generates the answer Ai by machine reading comprehension in an extractive mode or a generative mode using pre-trained model parameters is provided.
    Type: Grant
    Filed: May 28, 2019
    Date of Patent: July 2, 2024
    Assignee: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
    Inventors: Yasuhito Osugi, Itsumi Saito, Kyosuke Nishida, Hisako Asano, Junji Tomita
  • Publication number: 20240202495
    Abstract: A learning apparatus executes receiving a text and a question associated with the text, and calculating an evidence score expressing a likelihood of a character string included in the text as evidence for an answer to the question by using a model parameter of a first neural network; extracting, by sampling from a predetermined distribution having the evidence score as a parameter, a first set indicating a set of the character strings as the evidence for the answer from the text; receiving the question and the first set and extracting the answer from the first set by using a model parameter of a second neural network; and learning the model parameters of the first and second neural networks by calculating a gradient through error back propagation by using a continuous relaxation and a first loss between the answer and a true answer to the question.
    Type: Application
    Filed: March 6, 2020
    Publication date: June 20, 2024
    Applicant: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
    Inventors: Kosuke NISHIDA, Kyosuke NISHIDA, Itsumi SAITO, Hisako ASANO, Junji TOMITA
  • Publication number: 20240202442
    Abstract: A text generation apparatus includes a content selection unit that acquires a reference text based on an input text and information different from the input text and a generation unit that generates a text based on the input text and the reference text, wherein the content selection unit and the generation unit are neural networks based on learned parameters, so that information to be considered when generating a text can be added as text.
    Type: Application
    Filed: March 4, 2024
    Publication date: June 20, 2024
    Applicant: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
    Inventors: Itsumi SAITO, Kyosuke NISHIDA, Kosuke NISHIDA, Hisako ASANO, Junji TOMITA, Atsushi OTSUKA
  • Patent number: 11989976
    Abstract: A nonverbal information generation apparatus includes a nonverbal information generation unit that generates time-information-stamped nonverbal information that corresponds to time-information-stamped text feature quantities on the basis of the time-information-stamped text feature quantities and a learned nonverbal information generation model. The time-information-stamped text feature quantities are configured to include feature quantities that have been extracted from text and time information representing times assigned to predetermined units of the text. The nonverbal information is information for controlling an expression unit that expresses behavior that corresponds to the text.
    Type: Grant
    Filed: February 15, 2019
    Date of Patent: May 21, 2024
    Assignee: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
    Inventors: Ryo Ishii, Ryuichiro Higashinaka, Taichi Katayama, Junji Tomita, Nozomi Kobayashi, Kyosuke Nishida
  • Patent number: 11972365
    Abstract: A question generation device includes: generating means which uses a query and a relevant document including an answer to the query as input and, using a machine learning model having been learned in advance, generates a revised query in which a potentially defective portion of the query is supplemented with a word included in a prescribed lexical set.
    Type: Grant
    Filed: April 25, 2019
    Date of Patent: April 30, 2024
    Assignee: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
    Inventors: Atsushi Otsuka, Kyosuke Nishida, Itsumi Saito, Kosuke Nishida, Hisako Asano, Junji Tomita
  • Patent number: 11954435
    Abstract: A text generation apparatus includes a memory and a processor configured to execute acquiring a reference text based on an input text and information different from the input text; and generating a text based on the input text and the reference text, wherein the acquiring and the generating are implemented as neural networks based on learned parameters.
    Type: Grant
    Filed: March 3, 2020
    Date of Patent: April 9, 2024
    Assignee: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
    Inventors: Itsumi Saito, Kyosuke Nishida, Kosuke Nishida, Hisako Asano, Junji Tomita, Atsushi Otsuka
  • Publication number: 20240054295
    Abstract: A learning apparatus includes a memory and at least one processor connected to the memory, wherein the processor configured to: convert input text data into a feature amount sequence based on a language model; and update parameters of the language model based on the text data, the feature amount sequence, and a word vector learned in advance.
    Type: Application
    Filed: March 8, 2021
    Publication date: February 15, 2024
    Applicant: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
    Inventors: Kosuke NISHIDA, Kyosuke NISHIDA, Sen YOSHIDA
  • Patent number: 11893353
    Abstract: To make it possible to accurately generate a word vector even if vocabulary of a word vector data set is not limited. In a vector generating device 10 that generates vectors representing an input sentence P, when generating a series of the vectors representing the input sentence P based on vectors corresponding to words included in the input sentence P, a definition-sentence-considered-context encode unit 280 generates, based on a dictionary DB 230 storing sets of headwords y and definition sentences Dy, which are sentences defining the headwords y, concerning a word, which is the headword stored in the dictionary DB, among the words included in the input sentence P, the series of the vectors representing the input sentence P using the definition sentence Dy of the headwords y.
    Type: Grant
    Filed: March 4, 2019
    Date of Patent: February 6, 2024
    Assignee: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
    Inventors: Kosuke Nishida, Kyosuke Nishida, Hisako Asano, Junji Tomita
  • Publication number: 20230306202
    Abstract: A language processing apparatus includes: a preprocessing unit that splits an input text into a plurality of short texts; a language processing unit that calculates a first feature and a second feature using a trained model for each of the plurality of short texts; and an external storage unit configured to store a third feature for one or more short texts, and the language processing unit uses the trained model to calculate the second feature for a certain short text using the first feature of the short text and the third feature stored in the external storage unit.
    Type: Application
    Filed: August 20, 2020
    Publication date: September 28, 2023
    Applicant: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
    Inventors: Yasuhito OSUGI, Itsumi SAITO, Kyosuke NISHIDA, Hisako ASANO, Junji TOMITA
  • Patent number: 11704485
    Abstract: An appropriate vector of any phrase can be generated. A lattice construction unit 212 constructs a lattice structure formed by links binding adjacent word or phrase candidates based on a morphological analysis result and a dependency analysis result of input text. A first learning unit 213 performs learning of a neural network A for estimating nearby word or phrase candidates from word or phrase candidates based on the lattice structure. A vector generation unit 214 acquires a vector of each of the word or phrase candidates from the neural network A and sets the vector as learning data. A second learning unit performs learning of a neural network B for vectorizing the word or phrase candidates based on the learning data.
    Type: Grant
    Filed: February 15, 2019
    Date of Patent: July 18, 2023
    Assignee: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
    Inventors: Itsumi Saito, Kyosuke Nishida, Hisako Asano, Junji Tomita
  • Patent number: 11693854
    Abstract: This disclosure is provided, in which an answer generation unit configured to receive a document and a question as inputs, and execute processing of generating an answer sentence for the question by a learned model by using a word included in a union of a predetermined first vocabulary and a second vocabulary composed of words included in the document and the question, in which the learned model includes a learned neural network that has been learned in advance whether word included in the answer sentence is included in the second vocabulary, and increases or decreases a probability at which a word included in the second vocabulary is selected as the word included in the answer sentence at the time of generating the answer sentence by the learned neural network.
    Type: Grant
    Filed: March 27, 2019
    Date of Patent: July 4, 2023
    Assignee: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
    Inventors: Kyosuke Nishida, Atsushi Otsuka, Itsumi Saito, Hisako Asano, Junji Tomita
  • Publication number: 20230195723
    Abstract: An estimating device according to an embodiment includes a first input processing unit that takes a question sentence relating to a database and configuration information representing a configuration of the database as input, and creates first input data configured of the question sentence, a table name of a table stored in the database, a column name of a column included in the table of the table name, and a value of the column, and a first estimating unit that estimates whether or not a column name included in the first input data is used in an SQL query for searching the database for an answer with regard to the question sentence, using a first parameter that is trained in advance
    Type: Application
    Filed: May 20, 2020
    Publication date: June 22, 2023
    Inventors: Soichiro KAKU, Kyosuke NISHIDA, Junji TOMITA
  • Patent number: 11651166
    Abstract: A learning device of a phrase generation model includes a memory; and a processor configured to execute learning the phrase generation model including an encoder and a decoder, by using, as training data, a 3-tuple. The 3-tuple includes a combination of phrases and at least one of a conjunctive expression representing a relationship between the phrases, and a relational label indicating the relationship represented by the conjunctive expression. The encoder is configured to convert a phrase into a vector from a 2-tuple. The 2-tuple includes a phrase and at least one of the conjunctive expression and the relational label. The decoder is configured to generate, from the converted vector and the conjunctive expression or the relational label, a phrase having the relationship represented by the conjunctive expression or the relational label with respect to the phrase.
    Type: Grant
    Filed: February 22, 2019
    Date of Patent: May 16, 2023
    Assignee: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
    Inventors: Itsumi Saito, Kyosuke Nishida, Hisako Asano, Junji Tomita
  • Publication number: 20230130902
    Abstract: A text generation apparatus includes a processor and a memory storing program instructions that cause the processor to receive an input sentence including one or more words and generate a sentence: estimate an importance of each word included in the input sentence and encode the input sentence; and take the importance and a result of encoding the input sentence as inputs to generate the sentence based on the input sentence. The processor uses a neural network based on learned parameters. This improves the accuracy of sentence generation.
    Type: Application
    Filed: March 3, 2020
    Publication date: April 27, 2023
    Applicant: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
    Inventors: Itsumi SAITO, Kyosuke NISHIDA, Kosuke NISHIDA, Hisako ASANO, Junji TOMITA
  • Publication number: 20230076576
    Abstract: A learning device includes a memory; and a processor configured to execute answer generation means for taking data including text, and a question text related to the data as inputs; creating, by using a model parameter of a neural network, a token sequence that takes visual information in the data into consideration, and generating an answer text to the question text, based on the created token sequence; and learning means for learning the model parameter by using the answer text and a correct answer text to the question text.
    Type: Application
    Filed: December 9, 2020
    Publication date: March 9, 2023
    Applicant: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
    Inventors: Kyosuke NISHIDA, Ryota TANAKA, Sen YOSHIDA, Junji TOMITA
  • Publication number: 20230072537
    Abstract: A learning apparatus according to an embodiment has a feature generation means configured to take a search query, a first document related to the search query, and a second document that is not related to the search query as input, and generate a feature of the search query, a feature of the first document, and a feature of the second document, by using model parameters of a neural network, and an update means configured to take the feature of the search query, the feature of the first document, and the feature of the second document as input, and update the model parameters by using an error function including a cost function that is a differentiable approximation function of an L0 norm.
    Type: Application
    Filed: January 29, 2020
    Publication date: March 9, 2023
    Applicant: NIPPON TELEGRAPH AND TELEPHONE CORPORATION
    Inventors: Taku HASEGAWA, Kyosuke NISHIDA, Junji TOMITA, Hisako ASANO