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John A. Hawkins's Performance-Grammar Correspondence Hypothesis (PGCH) states that the syntactic structures of grammars are conventionalized based on whether and how much the structures are preferred in performance. [18] Performance preference is related to structure complexity and processing, or comprehension, efficiency. Specifically, a ...
As for adaptive performance, the more challenging (i.e., the less threatening) one's stress appraisals are, the more adaptive performance he/she would have. [14] This relationship is mediated by self-efficacy , which is a belief about one's capacities for certain tasks.
Shutt categorizes adaptive grammar models into two main categories: [3] [15] Imperative adaptive grammars vary their rules based on a global state changing over the time of the generation of a language. Declarative adaptive grammars vary their rules only over the space of the generation of a language (i.e., position in the syntax tree of the ...
The following table compares the number of languages which the following machine translation programs can translate between. (Moses and Moses for Mere Mortals allow you to train translation models for any language pair, though collections of translated texts (parallel corpus) need to be provided by the user.
Reverso has been active since 1998, with the aim of providing online translation and linguistic tools to corporate and mass markets. [3] [4] In 2013 it released Reverso Context, a bilingual dictionary tool based on big data and machine learning algorithms. [5] In 2016 Reverso acquired Fleex, a service for learning English via subtitled movies.
The first published English grammar was a Pamphlet for Grammar of 1586, written by William Bullokar with the stated goal of demonstrating that English was just as rule-based as Latin. Bullokar's grammar was faithfully modeled on William Lily's Latin grammar, Rudimenta Grammatices (1534), used in English schools at that time, having been ...
Google Translate previously first translated the source language into English and then translated the English into the target language rather than translating directly from one language to another. [11] A July 2019 study in Annals of Internal Medicine found that "Google Translate is a viable, accurate tool for translating non–English-language ...
MateCat ("Machine Translation Enhanced Computer Assisted Translation") is a 3-year research project (Nov 2011 – Oct 2014) funded by the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement No. 287688. [1] It has received over €2,500,000 of European funds. [2]