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Found 6 papers, 1 papers with code
Transfer Learning based Speech Affect Recognition in Urdu
Here we present a Transfer learning based Speech Affect Recognition approach in which: we pre-train a model for high resource language affect recognition task and fine tune the parameters for low resource language using Deep Residual Network.
An Attention Based Neural Network for Code Switching Detection: English & Roman Urdu
Code-switching is a common phenomenon among people with diverse lingual background and is widely used on the internet for communication purposes.
Bilingual Language Modeling, A transfer learning technique for Roman Urdu
We train Monolingual, Multilingual, and Bilingual models of Roman Urdu - the proposed bilingual model achieves 23% accuracy compared to the 2% and 11% of the monolingual and multilingual models respectively in the Masked Language Modeling (MLM) task.
Co-occurrences using Fasttext embeddings for word similarity tasks in Urdu
In this paper, we have built a corpus for Urdu by scraping and integrating data from various sources and compiled a vocabulary for the Urdu language.
RUBERT: A Bilingual Roman Urdu BERT Using Cross Lingual Transfer Learning
It is also a well-known fact that training and maintaining monolingual models for each language is a costly and time-consuming process.
NUBOT: Embedded Knowledge Graph With RASA Framework for Generating Semantic Intents Responses in Roman Urdu
The understanding of the human language is quantified by identifying intents and entities.
