David Chiang 蔣偉

Associate Professor, Computer Science and Engineering
Natural Language Processing Group

My research is in natural language processing, the subfield of computer science that aims to enable computers to understand and produce human language. I focus mainly on language translation, and am interested in syntactic parsing and other areas as well.


Recent publications

Tied Multitask Learning for Neural Speech Translation. Antonios Anastasopoulos and David Chiang, 2018. To appear in Proc. NAACL HLT.
Combining Character and Word Information in Neural Machine Translation Using a Multi-Level Attention. Huadong Chen et al., 2018. To appear in Proc. NAACL HLT.
Learning hyperedge replacement grammars for graph generation. Salvador Aguinaga, Tim Weninger, David Chiang, 2018. To appear in Trans. Pattern Analysis and Machine Intelligence.
Weighted DAG automata for semantic graphs. David Chiang, Frank Drewes, Adam Lopez, and Giorgio Satta, 2018. To appear in Computational Linguistics.
Incident-driven machine translation and name tagging for low-resource languages. Ulf Hermjakob et al., 2017. Machine Translation, 23 Oct 2017. PDF
Improving Lexical Choice in Neural Machine Translation. Toan Q. Nguyen and David Chiang, 2018. To appear in Proc. NAACL HLT. PDF
Transfer Learning across Low-Resource, Related Languages for Neural Machine Translation. Toan Q. Nguyen and David Chiang, 2017. In Proc. IJCNLP. PDF
Improved neural machine translation with a syntax-aware encoder and decoder. Huadong Chen, Shujian Huang, David Chiang, and Jiajun Chen. ACL 2017. PDF
Decoding with finite-state transducers on GPUs. Arturo Argueta and David Chiang. EACL 2017. PDF
An unsupervised probability model for speech-to-translation alignment of low-resource Languages. Antonios Anastasopoulos, Long Duong, and David Chiang, 2016. In Proc. EMNLP. PDF
An attentional model for speech translation without transcription. Long Duong, Antonios Anasatasopoulos, Trevor Cohn, Steven Bird, and David Chiang, 2016. In Proc. NAACL HLT. PDF
Auto-sizing neural networks: with applications to n-gram language models. Kenton Murray and David Chiang, 2015. In Proc. EMNLP. PDF
Kneser-Ney smoothing on expected counts. Hui Zhang and David Chiang, 2014. In Proc. ACL, 765–774. PDF
Decoding with large-scale neural language models improves translation. Ashish Vaswani, Yinggong Zhao, Victoria Fossum, and David Chiang, 2013. In Proc. EMNLP, 1387–1392. PDF
Parsing graphs with hyperedge replacement grammars. With Jacob Andreas, Daniel Bauer, Karl Moritz Hermann, Bevan Jones and Kevin Knight, 2013. In Proc. ACL, 924–932. PDF BibTeX

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