Samsung Electronics Co., Ltd.

Jangsu Lee

Jehun Jeon

GyuBum Han

Inkyu Choi

YoungMin Kim

Hoshik Lee

Woosuk Kim

Byungdeok Kim

Jiseung Jeong

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.

Method and apparatus with entity linking

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.

Method and apparatus for modeling user preferences

A distributed inference system includes an end device and a server. The end device generates status information and generates an inference result corresponding to target data based on a first machine learning model. The server creates a second machine learning model based on the status information and a training dataset including the inference result, calculates an accuracy of the inference result, and provides the second machine learning model to the end device based on the accuracy.

Distributed inference system and operating method of the same

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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Seoul, South Korea

Jangsu Lee