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Institution

The Chinese University of Hong Kong

EducationHong Kong, China
About: The Chinese University of Hong Kong is a education organization based out in Hong Kong, China. It is known for research contribution in the topics: Population & Cancer. The organization has 43411 authors who have published 93672 publications receiving 3066651 citations.


Papers
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Proceedings ArticleDOI
07 May 1996
TL;DR: In this paper, a state transition network is proposed to select and concatenate phonemes from a large speech database to produce a natural realisation of a target phoneme sequence predicted from text which is annotated with prosodic and phonetic context information.
Abstract: One approach to the generation of natural-sounding synthesized speech waveforms is to select and concatenate units from a large speech database. Units (in the current work, phonemes) are selected to produce a natural realisation of a target phoneme sequence predicted from text which is annotated with prosodic and phonetic context information. We propose that the units in a synthesis database can be considered as a state transition network in which the state occupancy cost is the distance between a database unit and a target, and the transition cost is an estimate of the quality of concatenation of two consecutive units. This framework has many similarities to HMM-based speech recognition. A pruned Viterbi search is used to select the best units for synthesis from the database. This approach to waveform synthesis permits training from natural speech: two methods for training from speech are presented which provide weights which produce more natural speech than can be obtained by hand-tuning.

1,207 citations

Journal ArticleDOI
TL;DR: A review of the existing entrepreneurship literature that employs institutional theory to understand the current status of the field, its current shortcomings, and where we need to move in the future can be found in this article.
Abstract: Institutional theory is an increasingly utilized theoretical lens for entrepreneurship research. However, while institutional theory has proven highly useful, its use has reached a point that there is a need to establish a clearer understanding of its wide-ranging application to entrepreneurship research. Therefore, we will initially review the existing entrepreneurship literature that employs institutional theory to both understand the current status of the field, its current shortcomings, and where we need to move in the future. We then summarize and discuss the articles in this special issue and how they contribute to this process of advancing institutional theory and its application in entrepreneurship research.

1,206 citations

Journal ArticleDOI
TL;DR: In this article, the authors test a theoretical framework relating four major corporate governance attributes with the extent of voluntary disclosure provided by listed firms in Hong Kong, including the proportion of independent directors to total number of directors on the board, the presence of a voluntary audit committee, the existence of a dominant personalities (CEO/Chairman duality), and the percentage of family members on the boards.

1,192 citations

Journal ArticleDOI
TL;DR: The definition of emotional intelligence was reviewed and it was argued that El is conceptually distinct from personality, and peer ratings were found to be significant predictors of job performance ratings provided by supervisors after controlling for the Big Five personality dimensions.
Abstract: In this study, the authors reviewed the definition of emotional intelligence (EI) and argued that El is conceptually distinct from personality. In Study 1, the authors showed that EI was related to yet distinct from personality dimensions and that it had incremental predictive power on life satisfaction. The authors examined the construct validity of self-reports and others' ratings of EI using two samples in Study 2. In a student sample, parents' ratings explained additional variance in the students' life satisfaction and feelings of powerlessness after controlling for the Big Five personality dimensions. In the work sample, peer ratings were found to be significant predictors of job performance ratings provided by supervisors after controlling for the Big Five personality dimensions. Other implications for future research on EI are discussed.

1,192 citations

Journal ArticleDOI
B. P. Abbott1, R. Abbott1, T. D. Abbott2, Sheelu Abraham3  +1271 moreInstitutions (145)
TL;DR: In 2019, the LIGO Livingston detector observed a compact binary coalescence with signal-to-noise ratio 12.9 and the Virgo detector was also taking data that did not contribute to detection due to a low SINR but were used for subsequent parameter estimation as discussed by the authors.
Abstract: On 2019 April 25, the LIGO Livingston detector observed a compact binary coalescence with signal-to-noise ratio 12.9. The Virgo detector was also taking data that did not contribute to detection due to a low signal-to-noise ratio, but were used for subsequent parameter estimation. The 90% credible intervals for the component masses range from to if we restrict the dimensionless component spin magnitudes to be smaller than 0.05). These mass parameters are consistent with the individual binary components being neutron stars. However, both the source-frame chirp mass and the total mass of this system are significantly larger than those of any other known binary neutron star (BNS) system. The possibility that one or both binary components of the system are black holes cannot be ruled out from gravitational-wave data. We discuss possible origins of the system based on its inconsistency with the known Galactic BNS population. Under the assumption that the signal was produced by a BNS coalescence, the local rate of neutron star mergers is updated to 250-2810.

1,189 citations


Authors

Showing all 43993 results

NameH-indexPapersCitations
Michael Marmot1931147170338
Jing Wang1844046202769
Jiaguo Yu178730113300
Yang Yang1712644153049
Mark Gerstein168751149578
Gang Chen1673372149819
Jun Wang1661093141621
Jean Louis Vincent1611667163721
Wei Zheng1511929120209
Rui Zhang1512625107917
Ben Zhong Tang1492007116294
Kypros H. Nicolaides147130287091
Thomas S. Huang1461299101564
Galen D. Stucky144958101796
Joseph J.Y. Sung142124092035
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023212
2022903
20217,888
20207,245
20195,968
20185,372