Search

Your search keyword '"Jung, Youngim"' showing total 7 results
Start Over Author "Jung, Youngim" Language english
7 results on '"Jung, Youngim"'

2. Commitment to Global Open Access Transition Collaboration: Outcomes and Lessons from SCOAP3- Korea

Author

Jung, Youngim and Kim, Hwanmin

Subjects
Information Transfer and Management
Abstract

Eight years have passed since the Sponsoring Consortium for Open Access Publishing in Particle Physics (SCOAP3) was launched. SCOAP3 is one of the most successful global partnerships and funds for Open Access and has been benchmarked by other Open Access initiatives. The Korea Institute of Science and Technology Information (KISTI) joined as the first Asian partner in 2011, and has supported its shared vision and contributed its financial commitment since the beginning of SCOAP3. SCOAP3-Korea is the first bottom-up collaboration for local libraries to re-direct funds previously used for subscriptions to Open Access publishing. This paper explores the roles and responsibilities of KISTI in the Open Access quest. It describes the commitment to SCOAP3 in South Korea, including how the collaboration model for SCOAP3-Korea differs from the global model. This paper also discusses the impact of SCOAP3-Korea by analyzing publications affiliated by Korean authors in SCOAP3 journals for the last six years (2014- 2019). We have integrated the national R&D; project and research outcome data from NTIS (National Science and Technology Information Service) to investigate the research articles benefited by SCOAP3 and research publications in non-SCOAP3 journals. The positive impact of SCOAP3 in increasing research publication in the discipline was revealed compared to non-SCOAP3 journals. In addition, the financial benefit of SCOAP3-Korea has been proven. With regard to the investment for readers, 137,094 USD was saved during the SCOAP3 Phase 1 and 2, while $748,923 USD was saved with regard to publication fees. We discussed the lessons from SCOAP3-Korea for commitment to a larger-scale Open Access transition.

Published
2022

5. Disambiguation Based on Wordnet for Transliteration of Arabic Numerals for Korean TTS.

Author

Gelbukh, Alexander, Jung, Youngim, Yoon, Aesun, and Kwon, Hyuk-Chul

Abstract

Transliteration of Arabic numerals is not easily resolved. Arabic numerals occur frequently in scientific and informative texts and deliver significant meanings. Since readings of Arabic numerals depend largely on their context, generating accurate pronunciation of Arabic numerals is one of the critical criteria in evaluating TTS systems. In this paper, (1) contextual, pattern, and arithmetic features are extracted from a transliterated corpus; (2) ambiguities of homographic classifiers are resolved based on the semantic relations in KorLex1.0 (Korean Lexico-Semantic Network); (3) a classification model for accurate and efficient transliteration of Arabic numerals is proposed in order to improve Korean TTS systems. The proposed model yields 97.3% accuracy, which is 9.5% higher than that of a customized Korean TTS system. [ABSTRACT FROM AUTHOR]

Published
2006
Full Text
View/download PDF

6. Formalization of Ontological Relations of Korean Numeral Classifiers.

Author

Jung, Youngim, Hwang, Soonhee, Yoon, Aesun, and Kwon, Hyuk-Chul

Abstract

Though many studies emphasized on the characteristics of numerals classifiers and the construction of database, or ontology of classifiers, few studies attempted to formalize them. This paper briefly presents preprocessing for the extraction of ontological relations from language resources, and formalizing those extracted relations with OWL DL. Then the overall result of building Korean numeral classifier ontology is illustrated. [ABSTRACT FROM AUTHOR]

Published
2006
Full Text
View/download PDF

7. Korean Prosody Phrase Boundary Prediction Model for Speech Synthesis Service in Smart Healthcare.

Author

Kim, Minho, Jung, Youngim, and Kwon, Hyuk-Chul

Subjects
SPEECH synthesis, DEEP learning, PROSODIC analysis (Linguistics), PREDICTION models, TERMS & phrases, SPEECH perception
Abstract

Speech processing technology has great potential in the medical field to provide beneficial solutions for both patients and doctors. Speech interfaces, represented by speech synthesis and speech recognition, can be used to transcribe medical documents, control medical devices, correct speech and hearing impairments, and assist the visually impaired. However, it is essential to predict prosody phrase boundaries for accurate natural speech synthesis. This study proposes a method to build a reliable learning corpus to train prosody boundary prediction models based on deep learning. In addition, we offer a way to generate a rule-based model that can predict the prosody boundary from the constructed corpus and use the result to train a deep learning-based model. As a result, we have built a coherent corpus, even though many workers have participated in its development. The estimated pairwise agreement of corpus annotations is between 0.7477 and 0.7916 and kappa coefficient (K) between 0.7057 and 0.7569. In addition, the deep learning-based model based on the rules obtained from the corpus showed a prediction accuracy of 78.57% for the three-level prosody phrase boundary, 87.33% for the two-level prosody phrase boundary. [ABSTRACT FROM AUTHOR]

Published
2021
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results