Fongbe ASR Dataset

Speech recognition dataset for Fongbe (fɔ̀ngbè), a Gbe language spoken by approximately 4.1 million people, primarily in Benin and Togo.

Dataset Description

This dataset contains read speech recordings in Fongbe with their transcriptions. It was originally collected by Fréjus A. A. Laleye and organized in the pyFongbe repository.

Statistics

Split	Samples	Duration	Speakers
train	8,234	~5.7h	23
test	2,168	~1.5h	4
total	10,402	~7.2h	27

Audio Format

• Format: WAV (PCM 16-bit)
• Sample rate: 16,000 Hz
• Channels: mono

Usage

from datasets import load_dataset

ds = load_dataset("alaleye/fon")

# Access a sample
sample = ds["train"][0]
print(sample["sentence"])   # Fongbe transcription
print(sample["audio"])      # {'array': np.array(...), 'sampling_rate': 16000}
print(sample["speaker"])    # Speaker name
print(sample["duration"])   # Duration in seconds

Streaming

ds = load_dataset("alaleye/fon", streaming=True)
for sample in ds["train"]:
    print(sample["sentence"])
    break

Features

• audio (Audio): audio waveform sampled at 16kHz
• sentence (string): Fongbe transcription
• speaker (string): speaker identifier
• duration (float64): audio duration in seconds

Speakers

Train set (23 speakers): armandine, boris, davacan, denise, dolores, donald, emmanuel, eunice, hans, herman, inconnu, lorseque, mario, melissa, miguel, mikael, narcisse, nazer, osias, parisius, rose, sorel, stephanie

Test set (4 speakers): antoine, cyrielle, frejus, helmut

Train and test speakers are disjoint, ensuring speaker-independent evaluation.

Source

• Repository: laleye/pyFongbe
• Related project: ALFFA (African Languages in the Field: speech Fundamentals and Automation)

Citation

If you use this dataset, please cite:

@inproceedings{laleye:hal-01436788,
  TITLE = {{First Automatic Fongbe Continuous Speech Recognition System: Development of Acoustic Models and Language Models}},
  AUTHOR = {Laleye, Fr{\'e}jus a A and Besacier, Laurent and Ezin, Eug{\`e}ne C and Motamed, Cina},
  URL = {https://hal.science/hal-01436788},
  BOOKTITLE = {{Proceedings of the Federated Conference on Computer Science and Information Systems}},
  ADDRESS = {Gdansk, Poland},
  VOLUME = {8},
  PAGES = {477 - 482},
  YEAR = {2016},
  MONTH = Sep,
  DOI = {10.15439/2016F153},
  KEYWORDS = { corpus ;  African languages ;  Fongbe ;  under-resourced languages ; automatic speech recognition (ASR)},
  PDF = {https://hal.science/hal-01436788v1/file/153.pdf},
  HAL_ID = {hal-01436788},
  HAL_VERSION = {v1},
}