In this paper, we present Bengali word embeddings and it's application in the classification
of news documents. Word embeddings are multi-dimensional vectors that can be created by …

In this paper, we describe a method for producing Bangla word clusters based on semantic
and contextual similarity. Word clustering is important for parts of speech (POS) tagging …

Clustering of words is the method that is used to partition the sets of words into subsets of
semantically similar words. Word clustering has crucial in many uses of natural language …

In this paper a new method for automatic word clustering is presented. We used this method
for building n-gram language models for Persian continuous speech recognition (CSR) …

Using word base n-gram language models in continuous speech recognition systems is so
prevalent. For using this type of language models, we should extract them from large …

Class-based n-gram language models are those most frequently-used in continuous speech
recognition systems, especially for languages for which no richly annotated corpora are …

Much research has been devoted to the task of learning lexical classes from unannotated
input text. Among the chief difficulties facing any approach to the unsupervised induction of …