michsethowusu/twi-words-speech-text-parallel

Twi Words Speech-Text Parallel Dataset

Dataset Description

This dataset contains 413463 parallel speech-text pairs for Twi (Akan), a language spoken primarily in Ghana. The dataset consists of audio recordings paired with their corresponding text transcriptions, making it suitable for automatic speech recognition (ASR) and text-to-speech (TTS) tasks.

Dataset Summary

• Language: Twi (Akan) - tw
• Task: Speech Recognition, Text-to-Speech
• Size: 413463 audio files > 1KB (small/corrupted files filtered out)
• Format: WAV audio files with corresponding text labels
• Modalities: Audio + Text

Supported Tasks

• Automatic Speech Recognition (ASR): Train models to convert Twi speech to text
• Text-to-Speech (TTS): Use parallel data for TTS model development
• Keyword Spotting: Identify specific Twi words in audio
• Phonetic Analysis: Study Twi pronunciation patterns

Dataset Structure

Data Fields

• audio: Audio file in WAV format
• text: Corresponding text transcription

Data Splits

The dataset contains a single training split with 413463 filtered audio files.

File Structure

Each audio segment is stored as a numbered pair:

• NNNN.wav: Audio file (e.g., 0001.wav)
• NNNN.txt: Corresponding text file (e.g., 0001.txt)

This structure ensures clean organization and easy pairing of audio-text data.

Dataset Creation

Source Data

The audio data has been sourced ethically from consenting contributors. To protect the privacy of the original authors and speakers, specific source information cannot be shared publicly.

Data Processing

1. Audio files were processed using forced alignment techniques
2. Word-level segmentation was performed with padding to prevent abrupt cuts
3. Audio segments were filtered based on:
   • Minimum duration requirements
   • Volume/vocal content thresholds
   • File size validation (> 1KB)
4. Each valid segment was saved as a numbered audio-text pair
5. Audio processing used the MMS-300M-1130 Forced Aligner tool for alignment and quality assurance

Quality Control

• Empty or silent audio segments were automatically filtered out
• Very short segments (< 200ms) were excluded
• Low-volume segments were removed to ensure vocal content
• Audio padding (100ms) was added to prevent abrupt word cuts

Annotations

Text annotations are stored in separate .txt files corresponding to each audio file, representing the exact spoken content in each audio segment.

Considerations for Using the Data

Social Impact of Dataset

This dataset contributes to the preservation and digital representation of Twi, supporting:

• Language technology development for underrepresented languages
• Educational resources for Twi language learning
• Cultural preservation through digital archives

Discussion of Biases

• The dataset may reflect the pronunciation patterns and dialects of specific regions or speakers
• Audio quality and recording conditions may vary across samples
• The vocabulary is limited to the words present in the collected samples

Other Known Limitations

• Limited vocabulary scope (word-level rather than sentence-level)
• Potential audio quality variations
• Regional dialect representation may be uneven
• Automatic filtering may have removed some valid segments

Additional Information

Licensing Information

This dataset is released under the Creative Commons Attribution 4.0 International License (CC BY 4.0).

Acknowledgments

• Audio processing and alignment performed using MMS-300M-1130 Forced Aligner
• The original audio is produced by The Ghana Institute of Linguistics, Literacy and Bible Translation in partnership with Davar Partners
• Automated quality filtering and padding applied to ensure high-quality audio segments

Citation Information

If you use this dataset in your research, please cite:

@dataset{twi_words_parallel_2025,
  title={Twi Words Speech-Text Parallel Dataset},
  year={2025},
  publisher={Hugging Face},
  howpublished={\url{https://huggingface.co/datasets/michsethowusu/twi-words-speech-text-parallel}}
}

Contact

For questions or concerns about this dataset, please open an issue in the dataset repository.

Usage Example

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("michsethowusu/twi-words-speech-text-parallel")

# Access audio and text pairs
for example in dataset["train"]:
    audio = example["audio"]
    text = example["text"]
    print(f"Text: {text}")
    print(f"Audio sample rate: {audio['sampling_rate']}")