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.
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