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The Social Origins of Language

By Daniel Dor

Presents a new theoretical framework for the origins of human language and sets key issues in language evolution in their wider context within biological and cultural evolution


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Preposition Placement in English: A Usage-Based Approach

By Thomas Hoffmann

This is the first study that empirically investigates preposition placement across all clause types. The study compares first-language (British English) and second-language (Kenyan English) data and will therefore appeal to readers interested in world Englishes. Over 100 authentic corpus examples are discussed in the text, which will appeal to those who want to see 'real data'


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Free Access 4 You

Free access to several Brill linguistics journals, such as Journal of Jewish Languages, Language Dynamics and Change, and Brill’s Annual of Afroasiatic Languages and Linguistics.


Academic Paper


Title: A fast and flexible architecture for very large word n-gram datasets
Author: Michael Flor
Institution: NLP and Speech Group
Linguistic Field: Computational Linguistics
Abstract: This paper presents TrendStream, a versatile architecture for very large word n-gram datasets. Designed for speed, flexibility, and portability, TrendStream uses a novel trie-based architecture, features lossless compression, and provides optimization for both speed and memory use. In addition to literal queries, it also supports fast pattern matching searches (with wildcards or regular expressions), on the same data structure, without any additional indexing. Language models are updateable directly in the compiled binary format, allowing rapid encoding of existing tabulated collections, incremental generation of n-gram models from streaming text, and merging of encoded compiled files. This architecture offers flexible choices for loading and memory utilization: fast memory-mapping of a multi-gigabyte model, or on-demand partial data loading with very modest memory requirements. The implemented system runs successfully on several different platforms, under different operating systems, even when the n-gram model file is much larger than available memory. Experimental evaluation results are presented with the Google Web1T collection and the Gigaword corpus.

CUP at LINGUIST

This article appears in Natural Language Engineering Vol. 19, Issue 1, which you can read on Cambridge's site or on LINGUIST .



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