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公开(公告)号:US20240176806A1
公开(公告)日:2024-05-30
申请号:US18464689
申请日:2023-09-11
Applicant: Samsung Electronics Co., Ltd.
Inventor: Jangsu LEE , Jehun JEON , Jiseung JEONG , Inkyu CHOI , GyuBum HAN
IPC: G06F16/33
CPC classification number: G06F16/334
Abstract: Disclosed is an entity linking method. A method includes: extracting an entity from an input context including text stored in a memory; obtaining candidate entities corresponding to, and based on, the extracted entity; determining a keyword based on the input context; generating keyword-based entity information based on the keyword and based on the extracted entity; and determining a top-matching entity corresponding to the entity based on the keyword-based entity information and the plurality of candidate entities.
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公开(公告)号:US20180130463A1
公开(公告)日:2018-05-10
申请号:US15625861
申请日:2017-06-16
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor: Jehun JEON , Jung-Hoe KIM
CPC classification number: G10L15/1815 , G06F16/3329 , G06F16/353 , G06F17/27 , G06F17/2785 , G06F17/279 , G10L15/02 , G10L15/063 , G10L15/14 , G10L15/16 , G10L15/18 , G10L15/22 , G10L2015/223
Abstract: An intention analysis apparatus includes an extractor configured to extract a feature value from a text input corresponding to machine recognition of an audio signal, a verifier configured to verify at least one state value associated with at least one of the text input or the audio signal, and a trained calculator configured to calculate a probability distribution of a user intention corresponding to the audio signal based on the feature value and the at least one state value.
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公开(公告)号:US20190164547A1
公开(公告)日:2019-05-30
申请号:US15992412
申请日:2018-05-30
Applicant: Samsung Electronics Co., Ltd.
Inventor: Sang Hyun YOO , Young-Seok KIM , Jeong-hoon PARK , Jehun JEON , Junhwi CHOI
Abstract: An electronic device and an method of the electronic device are provided, where the electronic device maintains a context that does not reflect a request for a secret conversation, in response to the request for the secret conversation being received from a first user, and generates a response signal to a voice signal of a second user based on the maintained context, in response to an end of the secret conversation with the first user.
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公开(公告)号:US20180061394A1
公开(公告)日:2018-03-01
申请号:US15686913
申请日:2017-08-25
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor: Jung-Hoe KIM , Jehun JEON , Kyoung Gu WOO
Abstract: A voice recognition apparatus and corresponding method include a processor configured to calculate a probability distribution corresponding to an intent associated with an utterance of a user by applying pre-stored training data to an input voice signal input based on the utterance. The processor is also configured to select a target feature extractor including either one or both of a training-based feature extractor and a rule-based feature extractor using the calculated probability distribution, and extract a feature associated with the utterance based on the selected target feature extractor.
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公开(公告)号:US20220092266A1
公开(公告)日:2022-03-24
申请号:US17186830
申请日:2021-02-26
Applicant: Samsung Electronics Co., Ltd.
Inventor: Inkyu CHOI , Jehun JEON , GyuBum HAN
Abstract: A method and device with natural language processing is disclosed. The method includes performing a word embedding of an input sentence, encoding a result of the word embedding, using an encoder of a natural language processing model, to generate a context embedding vector, decoding the context embedding vector, using a decoder of the natural language processing model, to generate an output sentence corresponding to the input sentence, generating a score indicating a relationship between the context embedding vector and each of a plurality of knowledge embedding vectors, determining a first loss based on the output sentence, determining a second loss based on the generated score, and performing training of the natural language processing model, including training the natural language processing model based on the determined first loss, and training the natural language processing model based on the determined second loss.
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公开(公告)号:US20210110817A1
公开(公告)日:2021-04-15
申请号:US17069927
申请日:2020-10-14
Applicant: Samsung Electronics Co., Ltd.
Inventor: Jangsu LEE , Hoshik LEE , Jehun JEON
IPC: G10L15/18 , G10L15/16 , G10L15/02 , G10L13/027
Abstract: A speech generation method and apparatus are disclosed. The speech generation method includes obtaining, by a processor, a linguistic feature and a prosodic feature from an input text, determining, by the processor, a first candidate speech element through a cost calculation and a Viterbi search based on the linguistic feature and the prosodic feature, generating, at a speech element generator implemented at the processor, a second candidate speech element based on the linguistic feature or the prosodic feature and the first candidate speech element, and outputting, by the processor, an output speech by concatenating the second candidate speech element and a speech sequence determined through the Viterbi search.
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公开(公告)号:US20190197121A1
公开(公告)日:2019-06-27
申请号:US16036076
申请日:2018-07-16
Applicant: Samsung Electronics Co., Ltd.
Inventor: Jehun JEON , Young-Seok KIM , Sang Hyun YOO , Junhwi CHOI
CPC classification number: G06F17/2881 , G10L13/02 , G10L15/16 , G10L15/1822 , G10L15/183 , G10L15/22 , G10L2015/225
Abstract: Provided is a processor-implemented method of generating a natural language, the method including generating a latent variable from an embedding vector that corresponds to an input utterance, determining attention information related to the input utterance by applying the generated latent variable to a neural network model, and outputting a natural language response that corresponds to the input utterance based on the calculated attention information.
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公开(公告)号:US20240232579A1
公开(公告)日:2024-07-11
申请号:US18524053
申请日:2023-11-30
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor: GyuBum HAN , Jehun JEON , Jangsu LEE , Jiseung JEONG , Inkyu CHOI
Abstract: A method of expanding a knowledge graph and an electronic device for performing the method are provided. The electronic device includes a processor and the processor is configured to train a first neural network to extract the triplet using the training data, to compare quality of the trained first neural network to a threshold value using the validation data, to extract a new triplet by inputting the text data to the trained first neural network, to measure a first confidence of the new triplet using the trained first neural network, to measure a second confidence of the new triplet using a trained second neural network using a triplet labeled to the training data and a triplet labeled to the validation data, and to expand the knowledge graph based on the first confidence and the second confidence.
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公开(公告)号:US20230126117A1
公开(公告)日:2023-04-27
申请号:US17698667
申请日:2022-03-18
Applicant: Samsung Electronics Co., Ltd.
Inventor: Jehun JEON , Jangsu LEE , Inkyu CHOI , GyuBum HAN
IPC: G06F16/9535
Abstract: A user preference modeling method including receiving preference scores corresponding to items, receiving an input for selecting an item from among the items, decaying a preference score corresponding to one or more items from among the items included in a first list and a second list based on a time decay rate and a first parameter, in response to the selected item being included in the first list, decaying the preference score corresponding to the one or more items comp included in the first list and the second list based on a time decay rate and a second parameter, in response to the selected item being included in the second list, and increasing a preference score corresponding to the selected item, wherein the first list may include one or more of the plurality of items based on the preference scores, and wherein the first list is different from the second list.
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公开(公告)号:US20220058433A1
公开(公告)日:2022-02-24
申请号:US17153011
申请日:2021-01-20
Applicant: Samsung Electronics Co., Ltd.
Inventor: GyuBum HAN , Jehun JEON , Inkyu CHOI
IPC: G06K9/62 , G06F40/295 , G06F40/30
Abstract: A method and apparatus for training an embedding vector generation model are provided, the method includes identifying a keyword in a query sentence, generating an embedding vector of the query sentence and an embedding vector of the keyword based on the embedding vector generation model, and training the embedding vector generation model such that a first similarity between the embedding vector of the query sentence and the embedding vector of the keyword is greater than a second similarity between an embedding vector of a reference sentence that does not include the keyword and the embedding vector of the keyword.
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