公开(公告)号：US20230061505A1

公开(公告)日：2023-03-02

申请号：US17885936

申请日：2022-08-11

申请人： Electronics and Telecommunications Research Institute

发明人： Yoo Rhee OH ,  Ki Young PARK ,  Jeon Gue PARK

IPC分类号： G10L15/06 ,  G10L15/30 ,  G06F40/166 ,  G10L15/02

摘要： The present invention relates to a method of training data augmentation for end-to-end speech recognition. The method for training data augmentation for end-to-end speech recognition includes: combining speech augmentation data and text augmentation data; performing a dynamic augmentation process on each of the speech augmentation data and the text augmentation data that have been combined; and training the end-to-end speech recognition using the speech augmentation data and the text augmentation data that are subjected to the dynamic augmentation process.

公开(公告)号：US20200175119A1

公开(公告)日：2020-06-04

申请号：US16671773

申请日：2019-11-01

申请人： ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

发明人： Eui Sok CHUNG ,  Hyun Woo KIM ,  Hwa Jeon SONG ,  Ho Young JUNG ,  Byung Ok KANG ,  Jeon Gue PARK ,  Yoo Rhee OH ,  Yun Keun LEE

IPC分类号： G06F17/28 ,  G06F17/27

摘要： Provided are sentence embedding method and apparatus based on subword embedding and skip-thoughts. To integrate skip-thought sentence embedding learning methodology with a subword embedding technique, a skip-thought sentence embedding learning method based on subword embedding and methodology for simultaneously learning subword embedding learning and skip-thought sentence embedding learning, that is, multitask learning methodology, are provided as methodology for applying intra-sentence contextual information to subword embedding in the case of subword embedding learning. This makes it possible to apply a sentence embedding approach to agglutinative languages such as Korean in a bag-of-words form. Also, skip-thought sentence embedding learning methodology is integrated with a subword embedding technique such that intra-sentence contextual information can be used in the case of subword embedding learning. A proposed model minimizes additional training parameters based on sentence embedding such that most training results may be accumulated in a subword embedding parameter.

公开(公告)号：US20180268739A1

公开(公告)日：2018-09-20

申请号：US15709686

申请日：2017-09-20

申请人： Electronics and Telecommunications Research Institute

发明人： Hoon CHUNG ,  Jeon Gue PARK ,  Yoo Rhee OH ,  Yun Kyung LEE ,  Yun Keun LEE

IPC分类号： G09B19/06 ,  G10L15/22 ,  G10L15/02 ,  G10L15/16 ,  G09B5/00

CPC分类号： G09B19/06 ,  G06N3/0454 ,  G06N3/084 ,  G09B5/00 ,  G09B7/00 ,  G10L15/02 ,  G10L15/16 ,  G10L15/22 ,  G10L25/30 ,  G10L25/60

摘要： Provided are end-to-end method and system for grading foreign language fluency, in which a multi-step intermediate process of grading foreign language fluency in the related art is omitted. The method provides an end-to-end foreign language fluency grading method of grading a foreign language fluency of a non-native speaker from a non-native raw speech signal, and includes inputting the raw speech to a convolution neural network (CNN), training a filter coefficient of the CNN based on a fluency grading score calculated by a human rater for the raw signal so as to generate a foreign language fluency grading model, and grading foreign language fluency for a non-native speech signal newly input to the trained CNN by using the foreign language fluency grading model to output a grading result.

公开(公告)号：US20210374545A1

公开(公告)日：2021-12-02

申请号：US17332464

申请日：2021-05-27

申请人： Electronics and Telecommunications Research Institute

发明人： Hyun Woo KIM ,  Jeon Gue PARK ,  Hwa Jeon SONG ,  Yoo Rhee OH ,  Byung Hyun YOO ,  Eui Sok CHUNG ,  Ran HAN

IPC分类号： G06N3/08 ,  G06N3/04 ,  G06F40/35 ,  G06N5/02 ,  G06N5/04

摘要： A knowledge increasing method includes calculating uncertainty of knowledge obtained from a neural network using an explicit memory, determining the insufficiency of the knowledge on the basis of the calculated uncertainty, obtaining additional data (learning data) for increasing insufficient knowledge, and training the neural network by using the additional data to autonomously increase knowledge.

公开(公告)号：US20210089904A1

公开(公告)日：2021-03-25

申请号：US17024062

申请日：2020-09-17

申请人： Electronics and Telecommunications Research Institute

发明人： Eui Sok CHUNG ,  Hyun Woo KIM ,  Hwa Jeon SONG ,  Yoo Rhee OH ,  Byung Hyun YOO ,  Ran HAN

IPC分类号： G06N3/08 ,  G06N3/04 ,  G06F17/18

摘要： The present invention provides a new learning method where regularization of a conventional model is reinforced by using an adversarial learning method. Also, a conventional method has a problem of word embedding having only a single meaning, but the present invention solves a problem of the related art by applying a self-attention model.