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Lexical Normalization
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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.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
A Weakly Supervised Data Labeling Framework for Machine Lexical Normalization in Vietnamese Social Media
ViLexNorm: A Lexical Normalization Corpus for Vietnamese Social Media Text
Automatic Textual Normalization for Hate Speech Detection
Mlphon: A Multifunctional Grapheme-Phoneme Conversion Tool Using Finite State Transducers
ÚFAL at MultiLexNorm 2021: Improving Multilingual Lexical Normalization by Fine-tuning ByT5
Contrastive String Representation Learning using Synthetic Data
Sequence-to-Sequence Lexical Normalization with Multilingual Transformers
DaN+: Danish Nested Named Entities and Lexical Normalization
User-Generated Text Corpus for Evaluating Japanese Morphological Analysis and Lexical Normalization
Lexical Normalization for Code-switched Data and its Effect on POS-tagging
A Clustering Framework for Lexical Normalization of Roman Urdu
Adapting Deep Learning for Sentiment Classification of Code-Switched Informal Short Text
A Multi-cascaded Deep Model for Bilingual SMS Classification
Adapting Sequence to Sequence models for Text Normalization in Social Media
MoNoise: Modeling Noise Using a Modular Normalization System
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