SOTAVerified

Lexical Normalization

Lexical normalization is the task of translating/transforming a non standard text to a standard register.

Example:

new pix comming tomoroe
new pictures coming tomorrow

Datasets usually consists of tweets, since these naturally contain a fair amount of these phenomena.

For lexical normalization, only replacements on the word-level are annotated. Some corpora include annotation for 1-N and N-1 replacements. However, word insertion/deletion and reordering is not part of the task.

Papers

Showing 3140 of 47 papers

TitleStatusHype
Modeling Input Uncertainty in Neural Network Dependency ParsingCode0
Noise-Robust Morphological Disambiguation for Dialectal Arabic0
A Taxonomy for In-depth Evaluation of Normalization for User Generated Content0
Handling Normalization Issues for Part-of-Speech Tagging of Online Conversational Text0
MoNoise: Modeling Noise Using a Modular Normalization SystemCode0
The Denoised Web Treebank: Evaluating Dependency Parsing under Noisy Input Conditions0
NCSU-SAS-Ning: Candidate Generation and Feature Engineering for Supervised Lexical Normalization0
IHS\_RD: Lexical Normalization for English Tweets0
NCSU\_SAS\_SAM: Deep Encoding and Reconstruction for Normalization of Noisy Text0
Shared Tasks of the 2015 Workshop on Noisy User-generated Text: Twitter Lexical Normalization and Named Entity Recognition0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MoNoiseAccuracy87.63Unverified
2Syllable basedAccuracy86.08Unverified
3TextNormAccuracy83.94Unverified
4unLOLAccuracy82.06Unverified