Electronics and Telecommunications Research Institute

Jong Hun Shin

Young Kil Kim

Jinxia Huang

Chang Hyun Kim

Ki Young Lee

Sang Kyu Park

Seong Il Yang

Young Ae Seo

Yoon Hyung Roh

Young-Ae Seo

Jeong Mu Heo

Oh Woog Kwon

Sung Kwon Choi

Yun Su Jin

Eun Jin Park

Soojong Lim

Seung Hoon Na

Jihee Ryu

Jin Seong

Sang Keun Jung

Provided is a method of generating a language model using crossmodal information. The method includes: receiving language-based first modality information and non-language-based second modality information; converting the first modality information into a first byte sequence; converting the second modality information into a second byte sequence; converting the first and second byte sequences into a first embedding vector and a second embedding vector by applying an embedding technique for each modality; generating semantic association information between first and second modality information by inputting the first and second embedding vectors to a crossmodal transformer; and learning the language model by setting the generated semantic association information as training data.

Method and apparatus for generating language model using crossmodal information

Provided is a method of providing an interpretation result using visual information, and the method includes: acquiring a spatial domain image including line-of-sight information of a user and gaze position information in the spatial domain image; segmenting the acquired spatial domain image into a plurality of images; detecting text areas including text for each of the segmented images; generating text blocks, each of which is a text recognition result for each of the detected text areas, and determining the text block corresponding to the gaze position information; converting a first language included in the determined text block into a second language that is a target language; and providing the user with a conversion result of the second language.

Method, apparatus, and system for providing interpretation result using visual information

A simultaneous interpretation system using a translation unit bilingual corpus includes a microphone configured to receive an utterance of a user, a memory in which a program for recognizing the utterance of the user and generating a translation result is stored, and a processor configured to execute the program stored in the memory, wherein the processor executes the program so as to convert the received utterance of the user into text, store the text in a speech recognition buffer, perform translation unit recognition with respect to the text on the basis of a learning model for translation unit recognition, and in response to the translation unit recognition being completed, generate a translation result corresponding to the translation unit on the basis of a translation model for translation performance.

Simultaneous interpretation system and method using translation unit bilingual corpus

The present invention provides a method of generating training data to which explicit word-alignment information is added without impairing sub-word tokens, and a neural machine translation method and apparatus including the method. The method of generating training data includes the steps of: (1) separating basic word boundaries through morphological analysis or named entity recognition of a sentence of a bilingual corpus used for learning; (2) extracting explicit word-alignment information from the sentence of the bilingual corpus used for learning; (3) further dividing the word boundaries separated in step (1) into sub-word tokens; (4) generating new source language training data by using an output from the step (1) and an output from the step (3); and (5) generating new target language training data by using the explicit word-alignment information generated in the step (2) and the target language outputs from the steps (1) and (3).

Neural machine translation method and apparatus

The present invention relates to a spoken dialog system and method based on dual dialog management using a hierarchical dialog task library that may increase reutilization of dialog knowledge by constructing and packaging the dialog knowledge based on a task unit having a hierarchical structure, and may construct and process the dialog knowledge using a dialog plan scheme about relationship therebetween by classifying the dialog knowledge based on a task unit to make design of a dialog service convenient, which is different from an existing spoken dialog system in which it is difficult to reuse dialog knowledge since a large amount of construction costs and time is required.

Spoken dialog system based on dual dialog management using hierarchical dialog task library

A method for establishing paraphrasing data for a machine translation system includes selecting a paraphrasing target sentence through application of an object language model to a translated sentence that is obtained by machine-translating a source language sentence, extracting paraphrasing candidates that can be paraphrased with the paraphrasing target sentence from a source language corpus DB, performing machine translation with respect to the paraphrasing candidates, selecting a final paraphrasing candidate by applying the object language model to the result of the machine translation with respect to the paraphrasing candidates, and confirming the paraphrasing target sentence and the final paraphrasing candidate as paraphrasing lexical patterns using a bilingual corpus and storing the paraphrasing lexical patterns in a paraphrasing DB. According to the present invention, the consistent paraphrasing data can be established since the paraphrasing data is automatically established.

Method for establishing paraphrasing data for machine translation system

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Daejeon, South Korea

Jong Hun Shin