CoolFace
Datasetpublic

zaneb-217/code-switching-codesaviours-si26-zaneb

Code-Switching Dataset – Code Saviours SI-26 Overview This dataset was created as part of the Code Saviours SI-26 ML/AI Internship for Roman Urdu code-switching detection. Description The dataset contains 150 manually created code-switched sentences. Each sentence is tokenized into individual words, and every word is assigned a language label. Data Collection The dataset was created by collecting Roman Urdu-English code-switching… See the full description on the dataset page: https://huggingface.co/datasets/zaneb-217/code-switching-codesaviours-si26-zaneb.

sourceHugging Facemitupdated 2mo agoView on Hugging Face
0likes5downloads
Dataset Card

Code-Switching Dataset – Code Saviours SI-26

Overview

This dataset was created as part of the Code Saviours SI-26 ML/AI Internship for Roman Urdu code-switching detection.

Description

The dataset contains 150 manually created code-switched sentences. Each sentence is tokenized into individual words, and every word is assigned a language label.

Data Collection

The dataset was created by collecting Roman Urdu-English code-switching sentences inspired by public social media conversations, educational discussions, and everyday chat-style text. Each sentence was manually tokenized into individual words, and every word was manually labeled as either ENG (English) or URD (Roman Urdu).

Labels

  • ENG – English word
  • URD – Roman Urdu word

Dataset Format

sentencewordlabel
Aaj ka din bohot busy thaAajURD
Aaj ka din bohot busy thabusyENG

Statistics

  • Total Sentences: 150
  • Total Word Entries: 862
  • Labels: ENG, URD

Applications

  • Code-switching detection
  • Token classification
  • NLP research
  • Roman Urdu language processing

Limitations

  • This dataset contains only 150 sentences.
  • It is intended for educational and research purposes.
  • It may not represent all Roman Urdu writing styles.

Future Work

  • Scale the dataset to 5,000+ images/sentences for production-level accuracy.
  • Add more domains such as social media, news, education, and conversations.
  • Include additional language labels for multilingual datasets.

Author

Zaneb Rasool Ahmed

Created during the Code Saviours SI-26 ML/AI Internship.