Meaning in Academic Book Reviews. English Text Construction 3(1). 95-119.
Römer, Ute and Matthew O’Donnell. 2009. Positional variation of phrase frames in a new corpus of proficient student writing. [Online] Paper presented at AACL conference. Edmonton, Canada, 9 Oct 2009. Available from: http://www.ualberta.ca/~aacl2009/PDFs/RoemerODonnell2009AACL.pdf. [Accessed: 15th September 2016].
Scott, Mike. 2008. Wordsmith Tools. Version 5. Oxford: Oxford University Press.
Sinclair, John. 2004. Trust the Text: Language, Corpus and
sequence similarity networks to identify partial cognates in multilingual wordlists”. In: Proceedings of the Association of Computational Linguistics 2016. (Volume 2: Short Papers.) Association of Computational Linguistics. 599-605.
List, J.-M., S. Greenhill and R. Gray. 2017. “The potential of automatic word comparison for historical linguistics”. PLOS ONE 12(1). 1-18.
List, J.-M. 2017. “A web-based interactive tool for creating, inspecting, editing, and publishing etymological datasets”. In: Proceedings of the 15th Conference of the
comparison of medical consultations with family and trained interpreters". Social Science and Medicine, 70, 1888-1895.
Mangione-Smith, Rita, Tanya Stivers, Marc Elliot et al. (2003). "Online commentaries during the physical examination: a communication tool for avoiding inappropriate antibiotic prescribing?" Social Science and Medicine, 56, 313-320.
Mead, Nicola & Peter Bower (2000). "Patient centredness: a conceptual framework and review of the empirical literature". Social Science and Medicine 51, 1087-1110.
Arkadiusz Rojczyk, Andrzej Porzuczek and Marcin Bergier
link between speech perception and production is phonological and abstract: Evidence form the shadowing task. Cognition 109: 168-173.
Munro, M. J., T. M. Derwing, J. E. Flege. 1999. Canadians in Alabama: A perceptual study of dialect acquisition in adults. Journal of Phonetics 27: 385-403.
Nagell, K., K. Olguin and M. Tomasello. 1993. Processes of social learning in tool use in chimpanzees ( Pan troglodytes ) and human children ( Homo sapiens ). Journal of Comparative Psychology . 107: 174-186.
Namy, L. L., L. C
sound patterns in vocal tract constraints”. In: Mac-Neilage, P.F. (ed.), The production of speech . New York: Springer-Verlag. 189–216.
Pisoni, D.B. 1973. “Auditory and phonetic memory codes in the discrimination of consonants and vowels”. Perception & Psychophysics 13. 253–216.
Psychology Software Tools, Inc. [E-Prime 2.0]. (2016). Retrieved from < http://www.pstnet.com >.
Redi, L. and S. Shattuck-Hufnagel. 2001. “Variation in the realization of glottalization in normal speakers”. Journal of Phonetics 29. 407–429.
Reynolds, B. 1994. “The
, Ji Yeon. “Postsecondary EFL Students’ Evaluations of Corpora with regard to English Writing.” The SNU Journal of Education Research , vol. 19, 2010, pp. 57-85.
Chang, Ji Yeon. The use of General and Specialized Corpora as Reference Tools for Academic and Technical English Writing: A Case Study of Korean Graduate Students of Engineering. Seoul National University, 2011.
Chun, Sooin. “Learners as Corpus Researchers: The Process of Developing Inductive Vocabulary learning through Hands-on Concordancing.” Doctoral Dissertation. Chung-Ang University
Hjerson: An Open Source Tool for Automatic Error Classification of Machine Translation Output
We describe Hjerson, a tool for automatic classification of errors in machine translation output. The tool features the detection of five word level error classes: morphological errors, reodering errors, missing words, extra words and lexical errors. As input, the tool requires original full form reference translation(s) and hypothesis along with their corresponding base forms. It is also possible to use additional information on the word level (e.g. pos tags) in order to obtain more details. The tool provides the raw count and the normalised score (error rate) for each error class at the document level and at the sentence level, as well as original reference and hypothesis words labelled with the corresponding error class in text and html formats.
Antonio Toral, Sudip Naskar, Federico Gaspari and Declan Groves
DELiC4MT: A Tool for Diagnostic MT Evaluation over User-defined Linguistic Phenomena
This paper demonstrates DELiC4MT, a piece of software that allows the user to perform diagnostic evaluation of machine translation systems over linguistic checkpoints, i.e., source-language lexical elements and grammatical constructions specified by the user. Our integrated tool builds upon best practices, software components and formats developed under different projects and initiatives, focusing on enabling easy adaptation to any language pair and linguistic phenomenon. We provide a description of the different modules that make up the tool, introduce a web demo and present a step-by-step case study of how it can be applied to a specific language pair and linguistic phenomenon.
Z-MERT: A Fully Configurable Open Source Tool for Minimum Error Rate Training of Machine Translation Systems
We introduce Z-MERT, a software tool for minimum error rate training of machine translation systems (Och, 2003). In addition to being an open source tool that is extremely easy to compile and run, Z-MERT is also agnostic regarding the evaluation metric, fully configurable, and requires no modification to work with any decoder. We describe Z-MERT and review its features, and report the results of a series of experiments that examine the tool's runtime. We establish that Z-MERT is extremely efficient, making it well-suited for time-sensitive pipelines. The experiments also provide an insight into the tool's runtime in terms of several variables (size of the development set, size of produced N-best lists, etc).