Understanding of human language by computers has been a central goal of Artificial Intelligence since its beginnings, with massive potential to improve communication, provide better information access and automate basic human tasks. My research focuses on technologies for automatic processing of human language, with several applications including automatic translation (akin to Google and Bing's translation tools). My core focus is on probabilistic machine learning modelling of language applications, particularly handling uncertain or partly observed data and structured prediction problems.

News

  • Melbourne will host ACL in July 2018, at the Melbourne Convention Centre, with Tim Baldwin, Karin Verspoor and myself serving as the local chairs.
  • Co-organising the ALTA 2016 workshop to be held in Monash Caulfield campus in Melbourne, on the 5th - 7th of December 2016. Please submit your papers by 30th September.
  • I'll be giving a tutorial on succinct data structures for NLP at COLING 2016 in Osaka, Japan on 12th December, 2016.

Current Projects

  • Efficient storage and access to text count data: An application to unlimited order language modelling. 2016 – 2017. Google Research Award, $US 85k.
  • Learning Deep Semantics for Automatic Translation between Human Languages. 2016 – 2019. ARC Discovery with Reza Haffari, $450k.
  • Ariel: Analysis of Rare Incident-Event Languages. 2015 – 2018. DARPA LORELEI (sub-contract), $300k.
  • Adaptive Context-Dependent Machine Translation for Heterogeneous Text. 2014 – 2018. ARC Future Fellowship, $730k.
  • Pheme: Computing Veracity Across Media, Languages, and Social Networks. 2014 – 2017. EU FP7 with Kalina Bontcheva and others, £494k.

Selected Papers

Fast, Small and Exact: Infinite-order Language Modelling with Compressed Suffix Trees
Ehsan Shareghi, Matthias Petri, Gholamreza Haffari and Trevor Cohn. In Transactions of ACL (TACL) (to be presented at EMNLP-16), 2016.
Abstract PDF Code
Learning Crosslingual Word Embeddings without Bilingual Corpora
Long Duong, Hiroshi Kanayama, Tengfei Ma, Steven Bird and Trevor Cohn. In Proceedings of EMNLP, 2016.
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Learning a Lexicon and Translation Model from Phoneme Lattices
Oliver Adams, Graham Neubig, Trevor Cohn, Steven Bird, Quoc Truong Do and Satoshi Nakamura. In Proceedings of EMNLP, 2016.
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Richer Interpolative Smoothing Based on Modified Kneser-Ney Language Modeling
Ehsan Shareghi, Trevor Cohn and Gholamreza Haffari. In Proceedings of EMNLP (short papers), 2016.
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Learning Robust Representations of Text
Yitong Li, Trevor Cohn and Timothy Baldwin. In Proceedings of EMNLP (short papers), 2016.
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Learning a Translation Model from Word Lattices
Oliver Adams, Graham Neubig, Trevor Cohn and Steven Bird. In Proceedings of Interspeech-16, 2016.
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Exploiting Tree Kernels for high performance Chemical Induced Disease relation extraction
Nagesh C. Panyam, Karin Verspoor, Trevor Cohn and Kotagiri Ramamohanarao. In Proceedings of International Symposium on Semantic Mining in Biomedicine (SMBM), 2016.
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SeeDev Binary Event Extraction using SVMs and a Rich Feature Set
Nagesh C. Panyam, Gitansh Khirbat, Karin Verspoor, Trevor Cohn and Kotagiri Ramamohanarao. In Proceedings of BioNLP-ST, 2016.
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Learning when to trust distant supervision: An application to low-resource POS tagging using cross-lingual projection
Meng Fang and Trevor Cohn. In Proceedings of CoNLL-16, 2016.
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Exploring Prediction Uncertainty in Machine Translation Quality Estimation,
Daniel Beck, Lucia Specia and Trevor Cohn. In Proceedings of CoNLL-16, 2016.
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Take and Took, Gaggle and Goose, Book and Read: Evaluating the Utility of Vector Differences for Lexical Relation Learning
Ekaterina Vylomova, Laura Rimell, Trevor Cohn and Timothy Baldwin. In Proceedings of ACL-16, 2016.
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pigeo: A Python Geotagging Tool
Afshin Rahimi, Trevor Cohn and Timothy Baldwin. In Proceedings of ACL-16 (Demonstrations), 2016.
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Hawkes Processes for Continuous Time Sequence Classification: An Application to Rumour Stance Classification in Twitter
Michal Lukasik, P.K. Srijith, Duy Vu, Kalina Bontcheva, Arkaitz Zubiaga and Trevor Cohn. In Proceedings of ACL-16 (Short papers), 2016.
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Incorporating Structural Alignment Biases into an Attentional Neural Translation Model
Trevor Cohn, Cong Duy Vu Hoang, Ekaterina Vylomova, Kaisheng Yao, Chris Dyer and Gholamreza Haffari. In Proceedings of NAACL-16, 2016.
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An Attentional Model for Speech Translation Without Transcription
Long Duong, Antonios Anastasopoulos, Steven Bird, David Chiang and Trevor Cohn. In Proceedings of NAACL-16, 2016.
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Incorporating Context into Recurrent Neural Network Language Models
Cong Duy Vu Hoang, Gholamreza Haffari and Trevor Cohn. In Proceedings of NAACL-16 (short), 2016.
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Document Context Language Models
Yangfeng Ji, Trevor Cohn, Lingpeng Kong, Chris Dyer, Jacob Eisenstein. In Proceedings of ICLR-16 Workshop, 2016.
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Convolution Kernels for Discriminative Learning from Streaming Text
Michal Lukasik and Trevor Cohn. In Proceedings of AAAI-16, 2016.
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