H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 47 Citations 8,348 256 World Ranking 3295 National Ranking 305

Research.com Recognitions

Awards & Achievements

2015 - IEEE Fellow For contributions to human-machine interactions

Overview

What is she best known for?

The fields of study she is best known for:

  • Artificial intelligence
  • Natural language processing
  • Machine learning

Pascale Fung mainly focuses on Artificial intelligence, Natural language processing, Speech recognition, Word and Parallel corpora. Her Artificial intelligence study frequently links to related topics such as Compiler. Her Natural language processing study frequently involves adjacent topics like Character.

Her Speech recognition study combines topics from a wide range of disciplines, such as Sentence, Pronunciation, Conversation and Mandarin Chinese. Pascale Fung has researched Word in several fields, including Terminology, Translation and Identity. The Parallel corpora study which covers Pattern matching that intersects with Noun phrase, Proper noun, Word lists by frequency, Noun and Dynamic time warping.

Her most cited work include:

  • An IR Approach for Translating New Words from Nonparallel, Comparable Texts (370 citations)
  • Statistical View on Bilingual Lexicon Extraction : From Parallel Corpora to Non-parallel Corpora (189 citations)
  • Compiling Bilingual Lexicon Entries From a Non-Parallel English-Chinese Corpus (158 citations)

What are the main themes of her work throughout her whole career to date?

Pascale Fung mainly investigates Artificial intelligence, Natural language processing, Speech recognition, Language model and Word. Her Artificial intelligence research is multidisciplinary, incorporating perspectives in Machine learning and Pattern recognition. Her biological study spans a wide range of topics, including Feature and Mixed language.

Pascale Fung has included themes like Pronunciation and Mandarin Chinese in her Speech recognition study. The Language model study combines topics in areas such as Code-switching, Cache language model, Factored language model and Code. Pascale Fung specializes in Word, namely Bilingual lexicon.

She most often published in these fields:

  • Artificial intelligence (66.57%)
  • Natural language processing (51.03%)
  • Speech recognition (39.59%)

What were the highlights of her more recent work (between 2018-2021)?

  • Artificial intelligence (66.57%)
  • Natural language processing (51.03%)
  • Language model (14.66%)

In recent papers she was focusing on the following fields of study:

Her scientific interests lie mostly in Artificial intelligence, Natural language processing, Language model, Machine learning and Word. Her Named-entity recognition research extends to the thematically linked field of Artificial intelligence. Her work deals with themes such as SemEval and Benchmark, which intersect with Natural language processing.

Her Language model research is included under the broader classification of Speech recognition. In general Speech recognition study, her work on Word error rate often relates to the realm of Transfer, thereby connecting several areas of interest. She combines subjects such as Sentence, Czech and Phrase with her study of Leverage.

Between 2018 and 2021, her most popular works were:

  • Transferable Multi-Domain State Generator for Task-Oriented Dialogue Systems (122 citations)
  • Personalizing Dialogue Agents via Meta-Learning (74 citations)
  • Transferable Multi-Domain State Generator for Task-Oriented Dialogue Systems (34 citations)

In her most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Natural language processing
  • Machine learning

Her primary areas of study are Artificial intelligence, Natural language processing, Language model, Code and Adaptation. Her work on Machine learning expands to the thematically related Artificial intelligence. Her Natural language processing research is multidisciplinary, incorporating perspectives in Word and Conversation.

Her Code research integrates issues from Question answering, Multi-document summarization, Information retrieval and Automatic summarization. Her Adaptation study incorporates themes from Dialog box, Joint and Word error rate. As a member of one scientific family, Pascale Fung mostly works in the field of Indonesian, focusing on Benchmark and, on occasion, Speech recognition.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

An IR Approach for Translating New Words from Nonparallel, Comparable Texts

Pascale Fung;Lo Yuen Yee.
meeting of the association for computational linguistics (1998)

567 Citations

A Statistical View on Bilingual Lexicon Extraction: From Parallel Corpora to Non-parallel Corpora

Pascale Fung.
conference of the association for machine translation in the americas (1998)

313 Citations

Statistical View on Bilingual Lexicon Extraction : From Parallel Corpora to Non-parallel Corpora

P. Fung.
Lecture Notes in Artificial Intelligence (1998)

291 Citations

K-vec: a new approach for aligning parallel texts

Pascale Fung;Kenneth Ward Church.
international conference on computational linguistics (1994)

237 Citations

Finding Terminology Translations from Non-parallel Corpora

Pascale Fung.
Journal of Visual Languages and Computing (1997)

233 Citations

Compiling Bilingual Lexicon Entries From a Non-Parallel English-Chinese Corpus

Pascale N. Fung.
meeting of the association for computational linguistics (1995)

213 Citations

Overview for the First Shared Task on Language Identification in Code-Switched Data

Thamar Solorio;Elizabeth Blair;Suraj Maharjan;Steven Bethard.
workshop on computational approaches to code switching (2014)

193 Citations

Mining Very-Non-Parallel Corpora: Parallel Sentence and Lexicon Extraction via Bootstrapping and E

Pascale Fung;Percy Cheung.
empirical methods in natural language processing (2004)

183 Citations

Mining Very-Non-Parallel Corpora: Parallel Sentence and Lexicon Extraction via Bootstrapping and EM

Pascale N. Fung;Percy Chi Shun Cheung.
Conference on Empirical Methods in NLP 2004, Barcelona, Span (2004)

172 Citations

The estimation of powerful language models from small and large corpora

P. Placeway;R. Schwartz;P. Fung;L. Nguyen.
international conference on acoustics, speech, and signal processing (1993)

164 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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