Hyperconnect Inc.

Seok Jun Seo

Beom Su Kim

Seung Ju Han

Enkhbayar Erdenee

Sang Il Ahn

Bu Ru Chang

Sang Bum Kim

Jin Yong Yoo

Dong Young Kim

Seung Woo Choi

Sung Joo Ha

Seok Hwan Choi

Su Hyun Lee

Yeon Woo Lee

Martin Kersner

Beom Jun Shin

Hyeong Keol Nam

Jae Hyeuk Oh

Se Yeon Oh

Sun Young Bae

Hyoun Taek Yong

A training method of a conversation model according to various example embodiments of the present disclosure may include identifying a first context, identifying a first response set corresponding to the first context based on a first model, identifying a response subset selected from the first response set based on a gold response corresponding to the first context and training a second model based on the first context information and the response subset.

Method of generating conversation information using examplar-based generation model and apparatus for the same

Disclosed is a method of training a dialogue model in an electronic device, the method including selecting a first context from a first dialogue data set including at least one pair of a context and a response corresponding to the context, generating a first response corresponding to the first context through a first dialogue model, generating an augmented dialogue dataset by incorporating a pair of the first context and the first response corresponding to the first context into the first dialogue data set, and training a second dialogue model based on the augmented dialogue dataset.

Dialogue model training method and device therefor

Systems and techniques to generate imitative responses are illustrated. response generation method performed in an electronic apparatus of the present disclosure includes acquiring at least one piece of utterance data, acquiring a first context corresponding to the utterance data from a context candidate set, generating one or more dialogue sets including the first context and the utterance data, receiving a second context from a user, and acquiring a response corresponding to the second context using a language model based on the one or more dialogue sets.

Method of generating response using utterance and apparatus therefor

A method of generating a reenacted image includes: extracting a landmark from each of a driver image and a target image; generating a driver feature map based on pose information and expression information of a first face shown in the driver image; generating a target feature map and a pose-normalized target feature map based on style information of a second face shown in the target image; generating a mixed feature map by using the driver feature map and the target feature map; and generating the reenacted image by using the mixed feature map and the pose-normalized target feature map.

Method and apparatus for generating reenacted image

Display screen or portion thereof with graphical user interface

A keyword spotting apparatus, method, and computer-readable recording medium are disclosed. The keyword spotting method using an artificial neural network according to an embodiment of the disclosure may include obtaining an input feature map from an input voice; performing a first convolution operation on the input feature map for each of n different filters having the same channel length as the input feature map, wherein a width of each of the filters is w1 and the width w1 is less than a width of the input feature map; performing a second convolution operation on a result of the first convolution operation for each of different filters having the same channel length as the input feature map; storing a result of the second convolution operation as an output feature map; and extracting a voice keyword by applying the output feature map to a learned machine learning model.

Keyword spotting apparatus, method, and computer-readable recording medium thereof

A server may include a communication interface for receiving a plurality of profile information from a plurality of terminals; and a processor configured to divide users of the plurality of terminals into a plurality of groups based on a first criterion, to divide users of a first gender included in each group into a plurality of subgroups based on a second criterion different from the first criterion, to divide users of a second gender different from the first gender, included in each group into a plurality of matching groups to correspond to each of the plurality of subgroups, and to provide profile information of users included in each of the plurality of matching groups corresponding to each of the plurality of subgroups among the plurality of profile information to users included in each of the plurality of subgroups.

Server of mediating a plurality of terminals, and mediating method thereof

Growing community of inventors

Seoul, South Korea

Seok Jun Seo