57 research outputs found
DravidianCodeMix: Sentiment Analysis and Offensive Language Identification Dataset for Dravidian Languages in Code-Mixed Text
This paper describes the development of a multilingual, manually annotated
dataset for three under-resourced Dravidian languages generated from social
media comments. The dataset was annotated for sentiment analysis and offensive
language identification for a total of more than 60,000 YouTube comments. The
dataset consists of around 44,000 comments in Tamil-English, around 7,000
comments in Kannada-English, and around 20,000 comments in Malayalam-English.
The data was manually annotated by volunteer annotators and has a high
inter-annotator agreement in Krippendorff's alpha. The dataset contains all
types of code-mixing phenomena since it comprises user-generated content from a
multilingual country. We also present baseline experiments to establish
benchmarks on the dataset using machine learning methods. The dataset is
available on Github
(https://github.com/bharathichezhiyan/DravidianCodeMix-Dataset) and Zenodo
(https://zenodo.org/record/4750858\#.YJtw0SYo\_0M).Comment: 36 page
Survey of Spell Checking Techniques for Malayalam: NLP
Abstract-Spell checking is a well-known task in Natural Language Processing. Nowadays, spell checkers are an important component of a number of computer software such as web browsers, word processors and others. Spelling error detection and correction is the process that will check the spelling of words in a document, and in occurrence of any error, list out the correct spelling in the form of suggestions. This survey paper covers different spelling error detection and correction techniques in various languages
Prediction of Part of Speech Tags for Punjabi using Support Vector Machines
Abstract: Part-of-Speech (POS
- …