Kevin Duh mainly focuses on Artificial intelligence, Natural language processing, Machine learning, Machine translation and Word. Kevin Duh performs multidisciplinary study in Artificial intelligence and Quality in his work. His studies deal with areas such as Context and Speech recognition as well as Natural language processing.
In his research, Word error rate is intimately related to Arabic, which falls under the overarching field of Speech recognition. Kevin Duh has included themes like Domain adaptation, Parsing and Adaptation in his Machine translation study. His Word research integrates issues from Preprocessor, BLEU, Set, Head and Syntax.
His primary areas of investigation include Artificial intelligence, Natural language processing, Machine translation, Machine learning and Word. His Artificial intelligence study frequently links to other fields, such as Speech recognition. The various areas that Kevin Duh examines in his Natural language processing study include Annotation and Arabic.
His Machine translation research is multidisciplinary, incorporating elements of Domain, Initialization and Rule-based machine translation. Kevin Duh interconnects Training set and Inference in the investigation of issues within Machine learning. As a member of one scientific family, Kevin Duh mostly works in the field of Word, focusing on Convolutional neural network and, on occasion, Spelling.
His scientific interests lie mostly in Artificial intelligence, Machine translation, Natural language processing, Machine learning and Translation. His work on Artificial intelligence is being expanded to include thematically relevant topics such as State. His Machine translation research is multidisciplinary, incorporating perspectives in Domain, Domain adaptation, Embedding and Initialization.
The Natural language processing study combines topics in areas such as End-to-end principle, Arabic and Meaning. In the subject of general Machine learning, his work in Hyperparameter, Deep learning and Artificial neural network is often linked to Sample, thereby combining diverse domains of study. Kevin Duh usually deals with Parsing and limits it to topics linked to Transduction and Graph and Speech recognition.
His primary areas of study are Artificial intelligence, Machine translation, Natural language processing, Machine learning and Comprehension. His Artificial intelligence study combines topics in areas such as Field and State. His Machine translation study incorporates themes from Domain adaptation, Domain and Initialization.
His Natural language processing research incorporates themes from Translation and Coreference. Kevin Duh works mostly in the field of Machine learning, limiting it down to topics relating to BLEU and, in certain cases, Word and Cross entropy. His Comprehension research focuses on Question answering and how it connects with Machine reading, Reinforcement learning, Robustness and Artificial neural network.
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DyNet: The Dynamic Neural Network Toolkit
Graham Neubig;Chris Dyer;Yoav Goldberg;Austin Matthews.
arXiv: Machine Learning (2017)
Representation Learning Using Multi-Task Deep Neural Networks for Semantic Classification and Information Retrieval
Xiaodong Liu;Jianfeng Gao;Xiaodong He;Li Deng.
north american chapter of the association for computational linguistics (2015)
Automatic Evaluation of Translation Quality for Distant Language Pairs
Hideki Isozaki;Tsutomu Hirao;Kevin Duh;Katsuhito Sudoh.
empirical methods in natural language processing (2010)
ReCoRD: Bridging the Gap between Human and Machine Commonsense Reading Comprehension.
Sheng Zhang;Xiaodong Liu;Jingjing Liu;Jianfeng Gao.
arXiv: Computation and Language (2018)
Stochastic Answer Networks for Machine Reading Comprehension
Xiaodong Liu;Yelong Shen;Kevin Duh;Jianfeng Gao.
meeting of the association for computational linguistics (2018)
Morphology-Based Language Modeling for Arabic Speech Recognition
Dimitra Vergyri;Katrin Kirchhoff;Kevin Duh;Andreas Stolcke.
conference of the international speech communication association (2004)
Morphology-based language modeling for conversational Arabic speech recognition
Katrin Kirchhoff;Dimitra Vergyri;Jeff A. Bilmes;Kevin Duh.
Computer Speech & Language (2006)
A framework for analyzing semantic change of words across time
Adam Jatowt;Kevin Duh.
acm/ieee joint conference on digital libraries (2014)
Learning to rank with partially-labeled data
Kevin Duh;Katrin Kirchhoff.
international acm sigir conference on research and development in information retrieval (2008)
Adaptation Data Selection using Neural Language Models: Experiments in Machine Translation
Kevin Duh;Graham Neubig;Katsuhito Sudoh;Hajime Tsukada.
meeting of the association for computational linguistics (2013)
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