Automatic Language Identification in Texts: A Survey
April 22, 2018 Β· The Cartographer Β· π Journal of Artificial Intelligence Research
"No code URL or promise found in abstract"
"Title-pattern auto-detect: Automatic Language Identification in Texts: A Survey"
Evidence collected by the PWNC Scanner
Authors
Tommi Jauhiainen, Marco Lui, Marcos Zampieri, Timothy Baldwin, Krister LindΓ©n
arXiv ID
1804.08186
Category
cs.CL: Computation & Language
Citations
221
Venue
Journal of Artificial Intelligence Research
Last Checked
1 day ago
Abstract
Language identification (LI) is the problem of determining the natural language that a document or part thereof is written in. Automatic LI has been extensively researched for over fifty years. Today, LI is a key part of many text processing pipelines, as text processing techniques generally assume that the language of the input text is known. Research in this area has recently been especially active. This article provides a brief history of LI research, and an extensive survey of the features and methods used so far in the LI literature. For describing the features and methods we introduce a unified notation. We discuss evaluation methods, applications of LI, as well as off-the-shelf LI systems that do not require training by the end user. Finally, we identify open issues, survey the work to date on each issue, and propose future directions for research in LI.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Computation & Language
π
π
Old Age
π
π
Old Age
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
π
π
Old Age
XLNet: Generalized Autoregressive Pretraining for Language Understanding
ποΈ
ποΈ
Transcended
Effective Approaches to Attention-based Neural Machine Translation
π
π
Old Age
A large annotated corpus for learning natural language inference
π
π
Old Age