Abstract Multi-class Sentiment Analysis (SA) is an important field of computational linguistics
that extracts multiple opinions expressed in a text using NLP and text-mining techniques …

Stemming is a program that matches the morphological variants of the word to its root word.
Stemming is extensively used as a pre-processing tool in the field of natural language …

We present OOD-Speech, the first out-of-distribution (OOD) benchmarking dataset for
Bengali automatic speech recognition (ASR). Being one of the most spoken languages …

Bengali is one of the most spoken languages in the world with over 300 million speakers
globally. Despite its popularity, research into the development of Bengali speech recognition …

Unsupervised morphological analysis is the task of segmenting words into prefixes, suffixes
and stems without prior knowledge of language-specific morphotactics and morpho …

The ability to identify important entities in a text, known as Named Entity Recognition (NER),
is useful in a large variety of downstream tasks in the biomedical domain. This is a …

A lemmatization algorithm for Bengali has been developed and evaluated. Its effectiveness
for word sense disambiguation (WSD) is also investigated. One of the key challenges for …

Lemmatization holds significance in both natural language processing (NLP) and linguistics,
as it effectively decreases data density and aids in comprehending contextual meaning …

The addition of inflectional suffixes in Bangla com-pound words is fairly complex. A
compound is a word that is formed by two or more different words acting as a single entity …

Part of Speech (POS) tagging is recognized as a significant research problem in the field of
Natural Language Processing (NLP). It has considerable importance in several NLP …