Datasets:

Orinode
/

naija-customer-call-code-switch

---
license: cc-by-4.0
task_categories:
  - text-generation
  - translation
language:
  - en
  - ha
  - yo
  - ig
size_categories:
  - 10K<n<100K
tags:
  - code-switching
  - nigerian
  - customer-service
  - low-resource
  - african-languages
  - hausa
  - yoruba
  - igbo
  - speech
  - asr
pretty_name: Naija Customer-Call Code-Switch Corpus
---

# Naija Customer-Call Code-Switch Corpus (Orinode-CCS)

Hand-written customer-service sentences with natural code-switching between Nigerian English and three indigenous Nigerian languages — **Hausa**, **Yoruba**, and **Igbo**. Covers 30+ business sectors typical of real customer-service calls in Nigeria.

Released by [Orinode](https://orinode.ai) under **CC-BY 4.0** to support research on multilingual ASR, NLU, and conversational AI for low-resource African languages.

---

## Why this dataset exists

Global voice-AI systems trip badly on Nigerian speech. Not because Nigerian languages are obscure — Hausa alone has ~80M native speakers — but because public datasets capturing the way Nigerians actually talk, especially the rapid mid-sentence code-switching between English and indigenous languages, are scarce.

This corpus targets that gap: 15,000 hand-written, naturalistic customer-service sentences a Nigerian would plausibly say to a call-center, broken down by language pair and code-switch ratio.

---

## Languages & sizes

| Pair | Code | Lines | Format |
|---|---|---:|---|
| Hausa ↔ English | `ha-en` | 5,000 | One sentence per line |
| Igbo ↔ English | `ig-en` | 5,000 | One sentence per line |
| Yoruba ↔ English | `yo-en` | 5,000 | One sentence per line |
| **Total** | | **15,000** | |

Yoruba sentences use full diacritics (ọ̀ ọ́ ẹ̀ ẹ́ ṣ etc.). Igbo sentences use standard orthography (ọ ụ ị ṅ). Hausa sentences use Latin orthography.

---

## Structure (9-section template per file)

Each file follows the same 9-section template so subsets can be cleanly extracted:

| Lines | Section | Style |
|---:|---|---|
| 1–500     | Gold seed | Natural mixed code-switch, balanced |
| 501–1000  | Target-leaning | ~70% indigenous language, ~30% English |
| 1001–2000 | Balanced | 50/50 split |
| 2001–3000 | English-leaning | ~70% English, ~30% indigenous |
| 3001–4000 | Natural mixed | Free mixing |
| 4001–4250 | Multi-turn snippets | Sequential lines = same caller |
| 4251–4500 | Government services | Passport, FRSC, NIMC, NEPA, customs |
| 4501–4750 | Legal / religious / security | Lawyer, mosque, church, NSCDC, embassy |
| 4751–5000 | Misc Nigerian specialty | Vet, funeral planner, photography, etc. |

The 30 core sectors used in lines 1–4000 include: restaurant, hotel, catering, bakery, event hall, supermarket, online shopping, fashion boutique, phone shop, pharmacy, hospital, dental, lab, salon, spa, gym, bank, microfinance, insurance, telecom, internet, cable TV, petrol/gas, ride-hailing, logistics, airline, mechanic, real estate, home services, education.

---

## File format

Plain UTF-8 text. One sentence per line, prefixed with its 1-indexed number:

```
1. <sentence>
2. <sentence>
...
5000. <sentence>
```

Sentence durations target **4–25 seconds** of spoken Nigerian speech at ~2.5 words/sec (so a 12-word line ≈ 5 sec; a 50-word line ≈ 20 sec). This makes the corpus directly suitable as ASR transcript prompts when paired with audio recordings.

---

## Sample sentences

**Hausa ↔ English:**
> Sannu, ina son in yi reservation for tonight, table for two at 7pm.

**Igbo ↔ English:**
> Ndewo, achọrọ m ka m book table for two at Genesis Restaurant Onitsha echi abalị.

**Yoruba ↔ English:**
> Bawo, mo fẹ́ book table for two at Nkoyo Lekki this Saturday evening.

---

## Intended use

- Multilingual ASR training (when paired with audio recordings)
- Code-switching detection and language identification
- Customer-service NLU and intent classification
- TTS prompt corpora for Nigerian languages
- Evaluation benchmarks for low-resource African speech systems
- Conversational-AI fine-tuning for Nigerian-market voice assistants

---

## Quality notes (honest internal assessment)

Quality is **not uniform** across the 5,000-line files. We are publishing the full corpus rather than only the high-quality subsets, so users can make their own filtering decisions.

| File | Lines 1–3000 | Lines 3001–4500 | Lines 4501–5000 |
|---|---|---|---|
| Hausa-English | Gold quality throughout | Gold quality | Gold quality |
| Igbo-English | Gold quality | Acceptable; templating in places | Weaker — some Hausa-language leakage, template loops |
| Yoruba-English | Gold quality | Acceptable | Weaker — ceremony/festival sections repetitive |

**Recommendation for downstream training:** prefer the first 3,000 lines of each file for highest-quality subsets. The middle and later sections (3001–5000) cover broader vocabulary (government, legal, religious, Nigerian specialty) but show more pattern repetition — useful for breadth, less so for quality benchmarks.

We welcome feedback and pull requests at [github.com/Orinode-ltd](https://github.com/Orinode-ltd).

---

## Methodology

These sentences were **authored by hand** — no LLM generation, no web scraping, no machine translation of monolingual corpora. Each sentence was written line-by-line by Nigerian-fluent contributors, then reviewed against the section ratio targets.

Code-switching follows natural Nigerian patterns: proper nouns (places, brands, currencies, numbers) stay in English even in target-language-heavy sentences; verbs and connectives follow the section ratio; greetings use the indigenous language (`Sannu`, `Ndewo`, `Bawo`).

---

## Limitations

- **Text only.** No audio. This is a transcript corpus. Audio recording is a planned follow-up.
- **Customer-service domain.** Not suitable as-is for general conversational AI in other domains (medical, legal, casual chat).
- **Lagos / Southwest / Igbo-East / Northern dialects of these languages exist** — the corpus reflects the standard written form most callers would use, not regional spoken variation.
- **No personal data.** All names, phone numbers, account numbers are fictional.

---

## Citation

If you use this dataset, please cite:

```bibtex
@misc{orinode_ccs_2026,
  title  = {Naija Customer-Call Code-Switch Corpus},
  author = {{Orinode Ltd}},
  year   = {2026},
  publisher = {Hugging Face},
  url    = {https://huggingface.co/datasets/Orinode/naija-customer-call-code-switch}
}
```

---

## License

**CC-BY 4.0** — free for commercial and non-commercial use with attribution.

---

## Contact

- Research: research@orinode.ai
- Partnerships: partnerships@orinode.ai
- Website: https://orinode.ai
- Org: https://huggingface.co/Orinode

Orinode Ltd · RC 9486856 · Lagos, Nigeria.