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Moazamzf/code-switching-codesaviours-si26-Moazam

Roman Urdu-English Code-Switching Dataset Description This dataset contains naturally occurring Roman Urdu / English code-switched sentences, collected to reflect how Pakistani speakers actually communicate online — mixing Roman Urdu and English within the same sentence (e.g. "Aaj mera mood nahi hai for anything"). Each sentence is broken down word-by-word, with every word labeled by language. Collection Method Sentences were collected from a mix of… See the full description on the dataset page: https://huggingface.co/datasets/Moazamzf/code-switching-codesaviours-si26-Moazam.

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Dataset Card

Roman Urdu-English Code-Switching Dataset

Description

This dataset contains naturally occurring Roman Urdu / English code-switched sentences, collected to reflect how Pakistani speakers actually communicate online — mixing Roman Urdu and English within the same sentence (e.g. "Aaj mera mood nahi hai for anything").

Each sentence is broken down word-by-word, with every word labeled by language.

Collection Method

Sentences were collected from a mix of sources including Pakistani Twitter/X, Reddit (r/pakistan), YouTube comments on Pakistani videos, and manually written examples reflecting common everyday code-switching patterns. Personal or identifying information was removed from any message-based sources.

Labels

Each word in a sentence is labeled as one of:

  • —URD — Roman Urdu word
  • —ENG — English word
  • —MIX — Hybrid/blended word combining both languages

Format

The dataset is provided as a flat CSV with three columns:

  • —sentence — the full original sentence
  • —word — an individual word from that sentence
  • —label — the language label for that word (URD / ENG / MIX)

Use Cases

This dataset can be used for code-switching detection, language identification, and NLP research on low-resource, informal, mixed-language text — a common but underrepresented pattern in South Asian digital communication.

Author

Collected as part of Project 2 for the Code Saviours ML/AI Internship (Batch SI-26) Moazam .