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15 Μαΐ 2024 · To help with Urdu language processing tasks, a new and robust preprocessing library called LughaatNLP has arisen as a vital tool for researchers, developers, and language fans alike. Table of Content. LughaatNLP. Key Features of LughaatNLP. 1. Tokenization. 2. Lemmatization. 3. Stop Word Removal. 4. Normalization. 5. Stemming. 6. Spell Checking. 7.
Google's service, offered free of charge, instantly translates words, phrases, and web pages between English and over 100 other languages.
This study presents the first version of the UNLT (Urdu Natural Language Toolkit) which contains three key text processing tools required for an Urdu NLP pipeline; word tokenizer, sentence tokenizer, and part-of-speech (POS) tagger.
A list of most frequently used Roman Urdu words with different spellings and usages to help make Roman Urdu text processing easier.
2 Ιουν 2016 · The core objective of this paper is to present a survey regarding different linguistic resources that exist for Urdu language processing, to highlight different tasks in Urdu language processing and to discuss different state of the art available techniques.
22 Αυγ 2024 · In this work, we leverage the sequence-to-sequence transformer model to translate Urdu (a low resourced language) to English. Our model is based on a variant of transformer with some changes as activation dropout, attention dropout and final layer normalization.
1 Μαρ 2017 · The core objective of this paper is to present a survey regarding different linguistic resources that exist for Urdu language processing, to highlight different tasks in Urdu language...
