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Evolutionary Syntax

By Ljiljana Progovac

This book "outlines novel and testable hypotheses, contains extensive examples from many different languages" and is "presented in accessible language, with more technical discussion in footnotes."

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The Making of Vernacular Singapore English

By Zhiming Bao

This book "proposes a new theory of contact-induced grammatical restructuring" and "offers a new analytical approach to New English from a formal or structural perspective."

Academic Paper

Title: Linguistic Knowledge in Statistical Phrase-based Word Alignment
Linguistic Field: Computational Linguistics; Text/Corpus Linguistics
Abstract: In this paper, a novel phrase alignment strategy combining linguistic knowledge and co-occurrence measures extracted from bilingual corpora is presented. The algorithm is mainly divided into four steps, namely phrase selection and classification, phrase alignment, one-to-one word alignment and post-processing. The first stage selects a linguistically-derived set of phrases that convey a unified meaning during translation and are therefore aligned together in parallel texts. These phrases include verb phrases, idiomatic expressions and date expressions. During the second stage, very high precision links between these selected phrases for both languages are produced. The third step performs a statistical word alignment using association measures and link probabilities with the remaining unaligned tokens, and finally the fourth stage takes final decisions on unaligned tokens based on linguistic knowledge. Experiments are reported for an English-Spanish parallel corpus, with a detailed description of the evaluation measure and manual reference used. Results show that phrase co-occurrence measures convey a complementary information to word co-occurrences and a stronger evidence of a correct alignment, successfully introducing linguistic knowledge in a statistical word alignment scheme. Precision, Recall and Alignment Error Rate (AER) results are presented, outperforming state-of-the-art alignment algorithms.


This article appears IN Natural Language Engineering Vol. 12, Issue 1, which you can READ on Cambridge's site or on LINGUIST .

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