7 citations · 36 across the 8 of their papers we have counts for
8 papers
Hierarchical Text Classification of Urdu News using Deep Neural Network
Taimoor Ahmed Javed, Waseem Shahzad, Umair Arshad
Digital text is increasing day by day on the internet. It is very challenging to classify a large and heterogeneous collection of data, which require improved information processin…
Transfer Learning based Speech Affect Recognition in Urdu
Sara Durrani, Muhammad Umair Arshad
It has been established that Speech Affect Recognition for low resource languages is a difficult task. Here we present a Transfer learning based Speech Affect Recognition approach…
Transfer learning from High-Resource to Low-Resource Language Improves Speech Affect Recognition Classification Accuracy
Sara Durrani, Umair Arshad
Speech Affect Recognition is a problem of extracting emotional affects from audio data. Low resource languages corpora are rear and affect recognition is a difficult task in cross-…
An Attention Based Neural Network for Code Switching Detection: English & Roman Urdu
Aizaz Hussain, Muhammad Umair Arshad
Code-switching is a common phenomenon among people with diverse lingual background and is widely used on the internet for communication purposes. In this paper, we present a Recurr…
RUBERT: A Bilingual Roman Urdu BERT Using Cross Lingual Transfer Learning
Usama Khalid, Mirza Omer Beg, Muhammad Umair Arshad
In recent studies, it has been shown that Multilingual language models underperform their monolingual counterparts. It is also a well-known fact that training and maintaining monol…
Bilingual Language Modeling, A transfer learning technique for Roman Urdu
Usama Khalid, Mirza Omer Beg, Muhammad Umair Arshad
Pretrained language models are now of widespread use in Natural Language Processing. Despite their success, applying them to Low Resource languages is still a huge challenge. Altho…
Co-occurrences using Fasttext embeddings for word similarity tasks in Urdu
Usama Khalid, Aizaz Hussain, Muhammad Umair Arshad +2
Urdu is a widely spoken language in South Asia. Though immoderate literature exists for the Urdu language still the data isn't enough to naturally process the language by NLP techn…
NUBOT: Embedded Knowledge Graph With RASA Framework for Generating Semantic Intents Responses in Roman Urdu
Johar Shabbir, Muhammad Umair Arshad, Waseem Shahzad
The understanding of the human language is quantified by identifying intents and entities. Even though classification methods that rely on labeled information are often used for th…