Compilation, Analysis and Application of a Comprehensive Bangla Corpus KUMono
Abstrak
Research in Natural Language Processing (NLP) and computational linguistics highly depends on a good quality representative corpus of any specific language. Bangla is one of the most spoken languages in the world but Bangla NLP research is in its early stage of development due to the lack of quality public corpus. This article describes the detailed compilation methodology of a comprehensive monolingual Bangla corpus, KUMono (Khulna University Monolingual corpus). The newly developed corpus consists of more than 350 million word tokens and more than one million unique tokens from 18 major text categories of online Bangla websites. We have conducted several word-level and character-level linguistic phenomenon analyses based on empirical studies of the developed corpus. The corpus follows Zipf’s curve and hapax legomena rule. The quality of the corpus is also assessed by analyzing and comparing the inherent sparseness of the corpus with existing Bangla corpora, by analyzing the distribution of function words of the corpus and vocabulary growth rate. We have developed a Bangla article categorization application based on the KUMono corpus and received compelling results by comparing to the state-of-the-art models.
Topik & Kata Kunci
Penulis (7)
A. Akther
Md. Shymon Islam
Hafsa Sultana
A. K. Z. Rasel Rahman
Sujan Kumar Saha
Kazi Masudul Alam
Rameswar Debnath
Akses Cepat
- Tahun Terbit
- 2022
- Bahasa
- en
- Total Sitasi
- 16×
- Sumber Database
- Semantic Scholar
- DOI
- 10.1109/access.2022.3195236
- Akses
- Open Access ✓