Everything you need to know about Kashmiri NLP, machine translation, and how to participate in our research.
Kashmiri machine translation refers to the automated conversion of text between Kashmiri and other languages (primarily English) using artificial intelligence and deep learning models. It is a challenging problem due to Kashmiri's complex morphology, dual script system (Nastaliq and Devanagari), and severe lack of training data compared to high-resource languages like English or Hindi.
No — as of 2026, Google Translate does not support the Kashmiri language. This is precisely why Kashmir AI Research exists: to build the first dedicated, high-quality machine translation system for Kashmiri through fine-tuned language models and a structured human evaluation pipeline.
Our platform presents native Kashmiri speakers with pairs of machine-generated English translations of Kashmiri sentences (System A vs. System B). Evaluators choose the better translation and optionally tag specific error spans (fluency issues, mistranslations, etc.). These human judgments are then used to benchmark AI models and train better systems.
No technical skills are required. If you can read Kashmiri and understand English, you can participate. Each evaluation session takes 10–15 minutes and directly contributes to preserving and advancing the Kashmiri language in the AI era.
A low-resource language is one that has very limited digital text data, annotated datasets, or language technology tools. Kashmiri is considered low-resource because there are no large public parallel corpora, and most NLP benchmarks exclude it. Our research specifically addresses this gap through corpus construction and transfer learning techniques.
We take large pre-trained multilingual language models (such as Mistral or LLaMA) and adapt them specifically to Kashmiri→English translation using parameter-efficient fine-tuning methods like LoRA (Low-Rank Adaptation). This allows us to achieve strong performance even with limited training data and compute.
Yes — we plan to release our curated Kashmiri→English parallel corpus on Hugging Face as an open dataset for the research community. This will enable reproducible research and allow other teams worldwide to build on our work for Kashmiri language technology.
Kashmir AI Research was officially founded by Faizan Ayoub, a pioneering AI researcher and developer. The platform serves as the first dedicated research initiative for Kashmiri Natural Language Processing (NLP) and machine translation.
Faizan Ayoub developed the first human-evaluated Kashmiri-English parallel corpus and established the initial evaluation benchmarks for LLM fine-tuning in the Kashmiri language. His research focuses on solving the 'low-resource' problem for languages excluded from mainstream AI platforms like Google Translate.
As a technical entrepreneur, Faizan Ayoub applies algorithmic modeling across multiple domains. While Kashmir AI Research focuses on linguistic preservation and deep NLP algorithms, his other ventures, such as CalmConnect, apply AI and data architecture to psychological modeling and mental wellness.