Poetry represents the oldest and most esteemed literary form, allowing poets to convey ideas while carefully attending to elements such as meaning, coherence, poetic quality, and fluency. Notably, the creation of good poetry entails considerations of ...

We present automatic speech recognition (ASR) systems for Tamil and Kannada based on subword modeling to effectively handle unlimited vocabulary arising due to the highly agglutinative nature of the languages. We propose a variant of the byte pair ...

Seal characters are derived from ancient Chinese pictographs, naturally inheriting pictographic characteristics and complex structures. As the essential components of seal characters, seal strokes play a vital role in seal character recognition, ...

In this work, we introduce WAFFNet, an attention-centric feature fusion architecture tailored for word-level multi-lingual scene text script identification. Motivated by the limitations of traditional approaches that rely exclusively on feature-based ...

Recently the field of sentiment analysis has gained a lot of attraction in literature. The idea that a machine can dynamically spot the text’s sentiments is fascinating. In this paper, we propose a method to classify the textual sentiments in Twitter ...

Within the context of video frame interpolation, complex motion modeling is the task of capturing, in a video sequence, where the moving objects are located in the interpolated frame, and how to maintain the temporal consistency of motion. Existing video ...

Internet users perceive a multilingual web but are unfamiliar with it due to communication in their regional language called Cross-Lingual Information Retrieval (CLIR). In CLIR, a translation technique is used to translate the user queries into the target ...

The rapid growth of Web 2.0, which enables people to generate, communicate, and share information, has resulted in an increase in the total number of users. In developing countries, online users’ sentiment influences decision-making, social views, ...

Word embeddings are widely deployed in a tremendous range of fundamental natural language processing applications and are also useful for generating representations of paragraphs, sentences, and documents. In some contexts involving constrained memory, it ...

We propose a new approach for Arabic Word Sense Disambiguation (AWSD) by hybridization of single-layer Convolutional Neural Network (CNN) with contextual representation (BERT). WSD is the task of automatically detecting the correct meaning of a word used ...

Real-time vehicle detection is a challenging and vital task in intelligent transportation systems. The key requirements for a vehicle detection model are speed and accuracy. However, existing real-time vehicle detection models often sacrifice one of these ...

Sentiment Analysis (SA) of medical reviews is crucial for improving healthcare outcomes. However, analyzing sentiment in low-resource languages such as Asian Hindi presents significant challenges. In this study, we propose an automatic graph construction ...

Question generation is an important task in natural language processing that involves generating questions from a given text. This paper proposes a novel approach for dynamic question generation using a context-aware auto-encoded graph neural model. Our ...

The rise of the digital economy and e-commerce has fostered a movement towards efficient low-resource medical information processing, a trend that holds great importance in the healthcare sector. Diabetes, being a widespread chronic condition, has ...

Machine translation has shown potential in improving access to medical information and healthcare services for multilingual patients. This research aims to enhance machine translation accuracy in the medical field, specifically for translating from Hindi ...

The rapid spread of fake news has become a serious concern over the internet. In recent years, social media platforms are widely used for news consumption. These platforms are excellent for their low-cost accessibility and rapid dissemination of news. ...

Data-driven supervised approaches rely on the parallel corpus. Due to lack of data and resources availability, it has become more difficult to achieve accurate outputs. In addition, the efficiency of the machine translation system depends on the quality ...

Low-resource languages are challenging to process intelligent decision systems due to limited data and resources. As an effective way of processing low-resource languages in intelligent decision systems, fuzzy linguistic approaches excel in transforming ...

‘‘Audiobook” is a multimedia-based reading technology that has emerged in recent years. Realizing the alignment of e-book text and book audio is the most important part of its processing. This article describes an audio and text alignment algorithm using ...

As a potential bilingual resource, loanwords play a very important role in many natural language processing tasks. If loanwords in a low-resource language can be identified effectively, the generated donor-receipt word pairs will benefit many cross-...