---
license: mit
language:
- ur
- en
tags:
- code-switching
- roman-urdu
- nlp
- pakistan
pretty_name: Code Switching Codesaviours SI26 - Muhammad Ahmad
---

# Code-Switching Codesaviours SI26 — Muhammad Ahmad

## Dataset Description

This dataset contains **155 naturally occurring Roman Urdu–English
code-switched sentences** (1,400+ word-level entries), reflecting how
Roman Urdu and English are mixed in everyday informal communication by
Pakistani speakers online (Twitter/X, WhatsApp, YouTube comments, Reddit).

Code-switching — alternating between two or more languages within a single
sentence or conversation — is extremely common in Pakistani digital
communication, but is poorly handled by most existing NLP models, which are
trained overwhelmingly on monolingual English or formal Urdu text.

## How it was collected

Sentences were sourced by observing genuine patterns of Roman Urdu–English
mixing common on Pakistani social media (Twitter/X, r/pakistan, YouTube
comments) and everyday informal chat, then written out and hand-labelled
word by word. This is a first version aimed at bootstrapping a resource
that does not currently exist in a clean, labelled form; a natural next
step is expanding it with directly scraped, timestamped social-media posts.

## Fields

| Column   | Description                                   |
|----------|------------------------------------------------|
| sentence | The full original mixed-language sentence       |
| word     | A single token from that sentence               |
| label    | The language label for that word (see below)    |

## Label meanings

- **URD** — Roman Urdu word (Urdu written in Latin script), e.g. `bohot`, `kya`, `hai`
- **ENG** — English word, e.g. `busy`, `meeting`, `honestly`
- **MIX** — an assimilated loanword that Pakistani speakers use
  interchangeably in both languages without treating it as a "foreign" word,
  e.g. `mobile`, `internet`, `data` (as in phone data)

## Intended Use

This dataset is intended for:
- Training/evaluating word-level language identification (LID) models for code-switched text
- Building or fine-tuning NLU models better suited to Roman Urdu–English text
- Linguistic research on code-switching patterns in South Asian digital communication

## Limitations

- Sample size (155 sentences) is a starting point, not a comprehensive corpus
- Sentences were authored/transcribed to reflect real usage patterns rather
  than scraped in bulk with timestamps/usernames; no personally identifiable
  information is included
- Label boundaries between MIX and ENG/URD can be subjective for heavily
  assimilated loanwords

## License

MIT