Tanglish-Corpus-185k

The largest Romanised Tamil-English code-mixed sentence corpus ever assembled — 185,973 clean sentences.

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Overview

This corpus contains 185,973 clean Tanglish sentences — Tamil and English mixed in Roman script, scraped from real Indian social media. It is 11.8x larger than DravidianCodeMix (15,744 sentences), the previous largest publicly available Tanglish corpus.

Built from scratch using a custom morphological filtering pipeline — no langdetect, no heuristic shortcuts. Every sentence passed through a 1,018-token Tamil lexicon and 27 morphological pattern filters designed specifically for Romanised code-mixed text.

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Why This Corpus Exists

Real tamil people type like this: "bro office ku late ah vanthen romba tired ah iruku"

"machan salary cut pannanga romba tension ah iruku"

"dei reels la time waste panniten assignment submit pannala"

"GPUku heat adhigam iruku cooling fix pannanum"

"amma cooking taste yarum beat pannala da"

No large-scale Romanised Tanglish corpus existed for training NLP models. Researchers working on Indian code-mixed NLP were limited to DravidianCodeMix (15,744 sentences) or synthetic data. This corpus fills that gap with real, diverse, multi-domain Tanglish from actual Indian social media.

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Corpus Statistics

Property	Value
Total sentences	185,973
vs DravidianCodeMix	11.8x larger
Script	Latin only (no Tamil Unicode)
Languages	Tamil + English code-mixed
Sources	YouTube (11 channels) + Reddit
Domains	8 distinct domains
Avg sentence length	~14 tokens
Filter yield rate	10.3% (from 1.8M raw comments)

Source breakdown:

Source	Raw Comments	Clean Sentences
YouTube — MadrasSamayal (cooking)	~150k	~18k
YouTube — AshwinRavi99 (cricket)	~120k	~14k
YouTube — TamilTechOfficial (tech)	~130k	~16k
YouTube — madangowri (info)	~140k	~15k
YouTube — Pdoggspeaks (commentary)	~110k	~12k
YouTube — manichoww (entertainment)	~120k	~13k
YouTube — News channels (3)	~400k	~35k
YouTube — Other channels (2)	~300k	~30k
Reddit r/TamilNaduDiscussion	~940	~300
DravidianCodeMix (Zenodo)	44,000	~32k
Total	1,806,024	185,973

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Filtering Pipeline

Why not langdetect?

langdetect completely fails on Tanglish. "romba boring ah iruku da this movie" gets classified as English. "nalla movie dhan bro climax twist" gets classified as Tagalog. Tamil grammar encoded in Latin script is invisible to character n-gram language detectors.

Our approach — morphological filtering:

Every raw comment passed through 5 gates:

1. Length filter — 5-60 tokens, minimum 15 characters
2. Tamil script rejection — drop sentences with >10% Tamil Unicode characters
3. Tamil pattern score — must match at least 1 of 27 morphological patterns
4. Tamil lexicon hits — must contain tokens from 1,018-token data-mined Tamil lexicon
5. Exact deduplication — lowercase exact match dedup across all sources

The lexicon was mined from data, not handcrafted: Frequency analysis on DravidianCodeMix → tokens appearing 20+ times absent from NLTK English dictionary → native speaker review → 1,018 Tamil-origin tokens.

The 27 morphological patterns cover:

• Case suffixes: -ku/-kku (dative), -la/-lla (locative), -oda (associative)
• Pannu verb family: workpannu, checkpanren, studypannitu
• Aagiduchu family: completeaagiduchu, finishaagiduchu
• Eh construction: scene eh vera, logic eh illa (uniquely Tanglish)
• Abbreviation+Tamil: GPUku, MLla, DSAva (tech Tanglish)

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Format

JSONL file. Each line is one sentence:

{"text": "Bro gymku poganum da romba lazy ah iruku", "source": "youtube/channel_id"}

Fields:

• text — clean Tanglish sentence
• source — origin (youtube/video_id or dravidiancodemix or reddit/subreddit)

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Sample Sentences

Bro office ku late ah vanthen romba tired ah iruku

Machan exam nerungudhu still prepare pannala tension ah iruku

Dei reels la time waste panniten assignment submit pannala

GPUku heat problem iruku cooling fix pannanum

Amma cooking taste yarum beat pannala da

College la attendance problem iruku sir kita pesanum

Instagram scroll panniten neram waste aagiduchi

Bro salary cut pannanga romba tension ah iruku

Semma movie da climax twist unexpected ah irundhuchu

Cricket match la last over la thrill ah irundhuchu

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How To Use

Load corpus

from datasets import load_dataset

dataset = load_dataset("vishnuexe/Tanglish-Corpus-185k")
print(dataset)
print(dataset['train'][0])

Use for training sentence embeddings

from datasets import load_dataset
from sentence_transformers import SentenceTransformer

dataset = load_dataset("vishnuexe/Tanglish-Corpus-185k")
sentences = [row['text'] for row in dataset['train']]

# use with SimCSE or TSDAE for unsupervised training
model = SentenceTransformer("your-base-model")

Filter by domain

from datasets import load_dataset

dataset = load_dataset("vishnuexe/Tanglish-Corpus-185k")

# filter YouTube only
yt_sentences = [row for row in dataset['train'] 
                if row['source'].startswith('youtube')]

# filter DravidianCodeMix only  
dc_sentences = [row for row in dataset['train']
                if row['source'] == 'dravidiancodemix']

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Limitations

• Domain bias — heavy representation of entertainment, cricket, and tech from YouTube channel selection
• Temporal bias — scraped June 2026; evolving slang not captured
• No labels — raw sentences only, no sentiment or topic labels
• Tanglish only — does not include Hinglish or other Indian code-mixed varieties
• Platform bias — YouTube and Reddit demographics skew young and urban

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Related Resources

• Model: vishnuexe/Morgan-Tanglish-v7 — sentence embedding model trained on this corpus
• Benchmark: vishnuexe/TanglishSTS — evaluation benchmark for Tanglish sentence similarity

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License

CC BY 4.0 — free for research and commercial use with attribution.

Data sources:

• YouTube public comments — YouTube Terms of Service (public data)
• Reddit public posts — Reddit Terms of Service (public data)
• DravidianCodeMix — CC BY 4.0 (Zenodo)

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Citation

@misc{vishnu2026tanglishcorpus,
  title={Tanglish-Corpus-185k: The Largest Romanised Tamil-English Code-Mixed Sentence Corpus},
  author={Vishnu N},
  year={2026},
  publisher={HuggingFace},
  url={https://huggingface.co/datasets/vishnuexe/Tanglish-Corpus-185k},
}

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About

Built by Vishnu N, B.E. CSE, Sri Sairam Institute of Technology, Chennai. Part of the IndianSentenceTransformer project.

HuggingFace: vishnuexe | GitHub: vishnu3105