State-of-the-art in Nepali NLP

The current research delves into the state-of-the-art of Natural Language Processing (NLP) tools and techniques specifically tailored for the Nepali language. This comprehensive review encompasses various aspects including the development of language corpora, language models featuring word embeddings, dependency parsing, and morphological analysis.

Problem:

Despite the increasing significance of NLP in various applications, the Nepali language lacks robust NLP resources and tools. Existing NLP techniques often fall short in effectively processing Nepali text due to limited availability of language-specific resources and models. This poses a significant challenge for the development of NLP applications tailored to Nepali language needs, hindering advancements in areas such as named entity recognition, sentiment analysis, and intent classification for chatbots.

Research Aim:

The primary objective of this research is to bridge the gap in Nepali NLP by conducting a thorough review of existing tools and techniques. By evaluating the current state-of-the-art in language corpora development, language models, dependency parsing, and morphological analysis, the aim is to identify areas for improvement and innovation. Additionally, the research aims to apply these insights to the development of NLP applications such as named entity recognition, sentiment analysis, and intent classification for chatbots, tailored specifically for the Nepali language context.

Outcome So Far:

The research has initiated a comprehensive review of existing NLP tools and techniques developed for the Nepali language. Preliminary findings have highlighted areas of strength and identified gaps in current approaches. The evaluation of language corpora, models, and parsing techniques has provided valuable insights into the challenges and opportunities in Nepali NLP. Moving forward, the research aims to leverage these insights to develop enhanced NLP applications tailored for Nepali, ultimately contributing to advancements in Nepali language processing.