jsbeaudry/finance-in-creole

Multi-Domain Haitian_creole Speech Dataset

This dataset contains 86 audio recordings with corresponding text transcriptions across multiple languages and domains.

Dataset Description

A comprehensive collection of audio files paired with text transcriptions, featuring both synthetic and natural speech across various domains. Suitable for automatic speech recognition (ASR), text-to-speech (TTS), and domain-specific speech processing tasks.

Dataset Structure

Each entry contains:

• id: Unique identifier (UUID)
• text: Transcription text in the specified language
• audio: URL to the audio file (with AWS S3 signed URLs)
• nature: Type of audio (e.g., "synthetic", "natural")
• language: Language of the audio/text
• domain: Domain/topic category (e.g., "agriculture", "healthcare", "education")

Languages

This dataset includes the following languages:

• Haitian_creole (ha): haitian_creole

Domains

Content spans across multiple domains:

• Finance: Domain-specific terminology and context

Audio Nature

The dataset includes different types of audio:

• Human: Natural human speech

Usage

from datasets import load_dataset
import json
import requests
from io import BytesIO
import pandas as pd

# Load using datasets library
dataset = load_dataset("jsbeaudry/finance-in-creole")

# Or load JSON directly
with open("dataset.json", "r", encoding="utf-8") as f:
    data = json.load(f)

print(f"Dataset contains {len(data)} audio-text pairs")

# Create DataFrame for analysis
df = pd.DataFrame(data)
print("\nDataset breakdown:")
print(f"Languages: {df['language'].value_counts().to_dict()}")
print(f"Domains: {df['domain'].value_counts().to_dict()}")
print(f"Nature: {df['nature'].value_counts().to_dict()}")

# Filter by criteria
swahili_agriculture = [item for item in data 
                      if item['language'] == 'swahili' and item['domain'] == 'agriculture']
print(f"\nSwahili agriculture samples: {len(swahili_agriculture)}")

# Example: Download and process audio
def download_audio(url):
    response = requests.get(url)
    return BytesIO(response.content)

# Get first audio file
audio_data = download_audio(data[0]['audio'])
print(f"Audio downloaded for: {data[0]['text'][:50]}...")

Sample Data

{
  "id": "12f53d3f-bb7c-40f2-ab8c-21c6d9c886f6",
  "source": "Jean",
  "text": "Lè ou fòme w sou finans pèsonèl, ou ka jwenn plis kontwòl sou lajan ou.",
  "audio": "https://voiceovers-haiti.s3.us-east-2.amazonaws.com/d4d942d2-0013-4035-839b-4bef4443d00c_d28cfdee-75e0-489a-a790-49db5343dd8a_human.wav?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=AKIAXF2BWYGA2CKJX4LH%2F20251006%2Fus-east-2%2Fs3%2Faws4_request&X-Amz-Date=20251006T175757Z&X-Amz-Expires=3600&X-Amz-Signature=ec2fae774150b2ece516124e368ec3efdc1eabb46dee815d8e8cf30936c56207&X-Amz-SignedHeaders=host&x-amz-checksum-mode=ENABLED&x-id=GetObject",
  "nature": "human",
  "language": "haitian_creole",
  "domain": "finance"
}

Sample Transcriptions by Domain

Finance Domain

1. Haitian_creole (human):
   "Lè ou fòme w sou finans pèsonèl, ou ka jwenn plis kontwòl sou lajan ou."
   ID: 12f53d3f...

2. Haitian_creole (human):
   "Si w ap peye dèt ou chak mwa, ou ka evite enterè ki vin ogmante plis chak jou."
   ID: 14926971...

Dataset Statistics

• Total audio files: 86
• Languages: 1 (Haitian_creole)
• Domains: 1 (finance)
• Audio types: human
• Average text length: 60 characters
• Audio hosting: voiceovers-haiti.s3.us-east-2.amazonaws.com

Distribution by Category

Category	Values
Haitian_creole	86 samples
Finance	86 samples
Human	86 samples

Audio Format

Audio files are stored locally in the dataset as WAV files. When loaded with the datasets library, audio is automatically converted to the standard format:

• Format: WAV
• Sampling Rate: Preserved from original (typically 16kHz or 22kHz)
• Channels: Mono
• Bit Depth: 16-bit or 32-bit float
• Access: Direct array access via dataset['train'][index]['audio']['array']

Use Cases

This dataset can be used for:

Speech Recognition (ASR)

• Multi-language speech recognition systems
• Domain-specific ASR models (agriculture, healthcare, etc.)
• Synthetic vs. natural speech detection

Text-to-Speech (TTS)

• Multi-language TTS systems
• Domain-adaptive speech synthesis
• Voice quality evaluation (synthetic vs. natural)

Research Applications

• Cross-domain speech analysis
• Language-specific phonetic studies
• Synthetic speech quality assessment
• Multi-modal AI training

Commercial Applications

• Voice assistants for specific domains
• Educational pronunciation tools
• Accessibility applications
• Multilingual customer service systems

Data Quality

• All audio files are accessible via HTTPS URLs with AWS authentication
• Text transcriptions are domain-verified and language-specific
• Unique identifiers ensure data integrity and traceability
• Consistent schema across all entries
• Balanced representation across domains and languages

License

This dataset is released under the MIT License.

Citation

@dataset{multi_domain_speech_2025,
  title={Multi-Domain Haitian_creole Speech Dataset},
  author={Dataset Creator},
  year={2025},
  languages={ha},
  domains={finance},
  url={https://huggingface.co/datasets/jsbeaudry/finance-in-creole}
}

Acknowledgments

Special thanks to contributors who provided audio recordings and transcriptions across multiple languages and domains to make this comprehensive dataset possible.