公开(公告)号：US20250124914A1

公开(公告)日：2025-04-17

申请号：US18734064

申请日：2024-06-05

Applicant: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

Inventor： Byung Ok Kang ,  Yoonhyung Kim ,  Hwajeon Song ,  HOON CHUNG

IPC: G10L15/06

Abstract: Provided is a method of training a speech recognizer based on shared and exclusive attributes. The method includes: inputting a parallel speech corpus constituting a labeled speech corpus and a non-parallel speech corpus into a speech encoder constituting a speech recognizer; outputting a representation vector representing training speech as an output of the speech encoder; inputting a parallel text corpus constituting the labeled speech corpus and a non-parallel text corpus into a text encoder; outputting a representation vector representing text as an output of the text encoder; and receiving and decoding, by a decoder, each of the representation vectors of the speech encoder and the text encoder.

公开(公告)号：US20240311560A1

公开(公告)日：2024-09-19

申请号：US18595675

申请日：2024-03-05

Applicant: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

Inventor： Joon Young Jung ,  Dong-oh Kang ,  Hwajeon Song

IPC: G06F40/205 ,  G06N3/0895

CPC classification number: G06F40/205 ,  G06N3/0895

Abstract: The present invention relates to an apparatus and method for deep learning-based coreference resolution using a dependency relation. An apparatus for deep learning-based coreference resolution according to the present invention includes a training data generation module that extracts one or more natural language sentences from a natural language paragraph and performs dependency parsing on the natural language sentences to generate dependency relation data of the natural language sentences, an embedding module that generates an integrated embedding vector for the natural language paragraph based on the natural language sentence and the dependency relation data, and a coreference resolution module that trains a deep learning neural network based on the integrated embedding vector and a first coreference mention preset for the natural language paragraph to generate a coreference resolution model.