| --- |
| 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). |
|
|
