---
language:
- bm
task_categories:
- text-generation
pretty_name: Bambara Text Normalization (Bamadaba)
size_categories:
- 1K<n<10K
tags:
- bambara
- text-normalization
---

# bm-text-normalization

Bambara (Bamanankan) orthographic normalisation: map a non-standard spelling to its
standard form. 4,877 short phrase-level pairs in a single config, `bamadaba`.

## Load

```python
from datasets import load_dataset

train = load_dataset("djelia/bm-text-normalization", "bamadaba", split="train")
dev   = load_dataset("djelia/bm-text-normalization", "bamadaba", split="dev")
test  = load_dataset("djelia/bm-text-normalization", "bamadaba", split="test")

# rows that are already correct — a model must not "fix" these
already_clean = train.filter(lambda row: row["noise_level"] == 0)
```

The validation split is named `dev`; `split="validation"` will fail.

## Splits

| Split | Rows |
| --- | ---: |
| `train` | 3,901 |
| `dev` | 488 |
| `test` | 488 |

## Fields

| Field | Description |
| --- | --- |
| `source_text` | Non-standard spelling |
| `target_text` | Standard-orthography form |
| `noise_level` | Character-level edit distance between the two, integer 0-25 |

Example rows:

| `source_text` | `target_text` | `noise_level` |
| --- | --- | ---: |
| `a bolira coyi !` | `a bolila coyi !` | 1 |
| `a be lajailen` | `a bɛɛ lajɛlen` | 4 |

## Notes

419 rows are identity pairs at `noise_level` 0 — text already correct, to be left alone.

The noise is a small closed inventory: Bambara characters replaced by what a French keyboard
produces (`ɛ`→`e`, `ɔ`→`o`, `ɲ`→`gn`), liquid confusion (`r`/`l`), plus deleted and inserted
spaces and dropped apostrophes (`k'a` written `ka`). Word boundaries move in both directions,
so a model has to join and split, not only map characters.

Sentences are short — median 19 characters. For running text such as ASR transcripts, see
[`djelia/bm-text-normalization-benchmark`](https://huggingface.co/datasets/djelia/bm-text-normalization-benchmark).