Lexical normalization is the task of transforming an utterance into its standardized form. This
task is beneficial for downstream analysis, as it provides a way to harmonize (often …

User generated texts on the web are freely-available and lucrative sources of data for
language technology researchers. Unfortunately, these texts are often dominated by …

In this paper, we introduce and demonstrate the online demo as well as the command line
interface of a lexical normalization system (MoNoise) for a variety of languages. We further …

Analyses of word embeddings have primarily focused on semantic and syntactic properties.
However, word embeddings have the potential to encode other properties as well. In this …

Lexical Normalization (LN) aims to normalize a nonstandard text to a standard text. This
problem is of extreme importance in natural language processing (NLP) when applying …

Social media is a valuable data resource for various natural language processing (NLP)
tasks. However, standard NLP tools were often designed with standard texts in mind, and …

Lexical normalization, a fundamental task in Natural Language Processing (NLP), involves
the transformation of words into their canonical forms. This process has been proven to …

While automatically computing numerical scores remains the dominant paradigm in NLP
system evaluation, error analysis is receiving increasing attention, with numerous error …

We present hinglishNorm--a human annotated corpus of Hindi-English code-mixed
sentences for text normalization task. Each sentence in the corpus is aligned to its …

The automatic analysis (parsing) of natural language is an important ingredient for many
natural language processing applications (search-engines, automatic translation, speech …