---
dataset_info:
- config_name: eng_Latn
  features:
  - name: sentenceId
    dtype: string
  - name: audio
    dtype: audio
  - name: transcription
    dtype: string
  splits:
  - name: train
    num_bytes: 1040719606.8972491
    num_examples: 5453
  - name: test
    num_bytes: 258927163.16460305
    num_examples: 1365
  download_size: 1304998398
  dataset_size: 1299646770.0618522
- config_name: kam_Latn
  features:
  - name: sentenceId
    dtype: string
  - name: audio
    dtype: audio
  - name: transcription
    dtype: string
  splits:
  - name: train
    num_bytes: 949154503.8526143
    num_examples: 5453
  - name: test
    num_bytes: 231674860.6190823
    num_examples: 1365
  download_size: 1050210487
  dataset_size: 1180829364.4716966
- config_name: kik_Latn
  features:
  - name: sentenceId
    dtype: string
  - name: audio
    dtype: audio
  - name: transcription
    dtype: string
  splits:
  - name: train
    num_bytes: 999271913.2047732
    num_examples: 5453
  - name: test
    num_bytes: 251070401.12163147
    num_examples: 1365
  download_size: 1102853572
  dataset_size: 1250342314.3264046
- config_name: luo_Latn
  features:
  - name: sentenceId
    dtype: string
  - name: audio
    dtype: audio
  - name: transcription
    dtype: string
  splits:
  - name: train
    num_bytes: 1002213254.8480598
    num_examples: 5453
  - name: test
    num_bytes: 250754022.3561544
    num_examples: 1365
  download_size: 1136906561
  dataset_size: 1252967277.204214
- config_name: mer_Latn
  features:
  - name: sentenceId
    dtype: string
  - name: audio
    dtype: audio
  - name: transcription
    dtype: string
  splits:
  - name: train
    num_bytes: 965387013.9227546
    num_examples: 5453
  - name: test
    num_bytes: 238541793.85651857
    num_examples: 1365
  download_size: 1092296070
  dataset_size: 1203928807.7792733
- config_name: som_Latn
  features:
  - name: sentenceId
    dtype: string
  - name: audio
    dtype: audio
  - name: transcription
    dtype: string
  splits:
  - name: train
    num_bytes: 1006695041.671707
    num_examples: 5453
  - name: test
    num_bytes: 251778992.20684633
    num_examples: 1365
  download_size: 1131486202
  dataset_size: 1258474033.8785534
configs:
- config_name: eng_Latn
  data_files:
  - split: train
    path: eng_Latn/train-*
  - split: test
    path: eng_Latn/test-*
- config_name: kam_Latn
  data_files:
  - split: train
    path: kam_Latn/train-*
  - split: test
    path: kam_Latn/test-*
- config_name: kik_Latn
  data_files:
  - split: train
    path: kik_Latn/train-*
  - split: test
    path: kik_Latn/test-*
- config_name: luo_Latn
  data_files:
  - split: train
    path: luo_Latn/train-*
  - split: test
    path: luo_Latn/test-*
- config_name: mer_Latn
  data_files:
  - split: train
    path: mer_Latn/train-*
  - split: test
    path: mer_Latn/test-*
- config_name: som_Latn
  data_files:
  - split: train
    path: som_Latn/train-*
  - split: test
    path: som_Latn/test-*
pretty_name: thiomi_5k_v1
language:
- eng
- kik
- kam
- luo
- mer
- som
tags:
- speech
- audio
- tts
- asr
- multilingual
- low-resource
- african-languages
task_categories:
- automatic-speech-recognition
- text-to-speech
size_categories:
- 10K<n<100K
---


# Thiomi 5k


## Motivation

This dataset release is part of the data and modeling effort described in: **[The Thiomi Dataset: A Large-Scale Multimodal Corpus for Low-Resource African Languages](https://arxiv.org/abs/2603.29244)**


The broader Thiomi work focuses on building high-quality multimodal resources for
African languages and enabling ASR/MT/TTS research and deployment.

## Data Structure

Per language config (`eng_Latn`, `kik_Latn`, `kam_Latn`, `luo_Latn`, `mer_Latn`, `som_Latn`):

Each config contains `train` and `test` splits. Every row has three fields:
`sentenceId` (string), `audio` (HF `Audio` feature), and `transcription` (string).
Row counts are identical across all language configs within a split — the 44
previously-missing English sentences have been removed from every language.

## Dataset Statistics

| Config | Language | Train Samples | Test Samples | Train Audio (h) | Test Audio (h) |
|---|---|---:|---:|---:|---:|
| `eng_Latn` | English | 5,453 | 1,365 | 6.59 | 1.64 |
| `kik_Latn` | Kikuyu  | 5,453 | 1,365 | 8.62 | 2.17 |
| `kam_Latn` | Kamba   | 5,453 | 1,365 | 8.21 | 2.00 |
| `luo_Latn` | Luo     | 5,453 | 1,365 | 8.65 | 2.16 |
| `mer_Latn` | Kimeru  | 5,453 | 1,365 | 8.34 | 2.06 |
| `som_Latn` | Somali  | 5,453 | 1,365 | 8.69 | 2.17 |
| **Total**  |         | **32,718** | **8,190** | **49.10** | **12.21** |


## Intended Uses

- TTS training and adaptation per language
- ASR training/evaluation with language-specific subsets
- Speech-text alignment and multilingual benchmarking
- Data selection and curriculum design for low-resource speech systems

## Limitations

- English audio was generated via TTS, not recorded by human speakers.
- Language balance by *hours* differs despite approximately equal row counts.

## Privacy and Ethics

Please follow applicable consent, privacy, and data governance requirements from
the upstream collection and platform process described in the Thiomi paper.

## Citation

If you use this dataset, please cite the Thiomi dataset paper:

```bibtex
@misc{mutisya2026thiomidatasetlargescalemultimodal,
      title={The Thiomi Dataset: A Large-Scale Multimodal Corpus for Low-Resource African Languages}, 
      author={Hillary Mutisya and John Mugane and Gavin Nyamboga and Brian Chege and Maryruth Gathoni},
      year={2026},
      eprint={2603.29244},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2603.29244}, 
}
```

## Acknowledgements

Thanks to the Thiomi contributors, speakers, annotators, and reviewers who made
multilingual speech data collection and curation possible.