Automatic spelling correction has been receiving sustained research attention. Although
each article contains a brief introduction to the topic, there is a lack of work that would …

The pre-trained language models (PLMs), such as BERT, have been successfully employed
in two-phases ranking pipeline for information retrieval (IR). Meanwhile, recent studies have …

In contrast with the research of new models, little attention has been paid to the impact of low
or high-quality data feeding a dialogue system. The present paper makes the first attempt to …

Spelling errors are a prevalent form of interference that may result from human handwriting
or natural language processing systems, such as optical character recognition. This type of …

Traditional Optical Character Recognition (OCR) systems that generate text of highly
inflectional Indic languages like Hindi tend to suffer from poor accuracy due to a wide …

Query-by-example spoken document retrieval (QbESDR) aims at finding those documents in
a set that include a given spoken query. Current approaches are, in general, not valid for …

Modern large language models demonstrate impressive capabilities in text generation and
generalization. However, they often struggle with solving text editing tasks, particularly when …

This paper describes the development and testing of a novel Automatic Search Query
Enhancement (ASQE) algorithm, the Wikipedia N Sub-state Algorithm (WNSSA), which …

When knowledge is developed fast, as it is the case so often nowadays, one of the main
difficulties in initiating new research in any field is to identify the domain's specific state-of …

In a context of digitalization and modernization of healthcare, automatic analysis of clinical
data plays a leading role in improving the quality of care. Since much of the information lies …