michsethowusu/twi-words-speech-text-parallel-multispeaker

Twi Words Speech-Text Parallel Dataset

Dataset Description

This dataset contains 340908 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: 340908 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 340908 filtered audio files.

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 collected and organized by filename structure
2. Text labels were extracted from filenames (format: [number]_[text].wav)
3. Files smaller than 1KB were filtered out to ensure audio quality
4. Audio was processed using the MMS-300M-1130 Forced Aligner tool for alignment and quality assurance

Annotations

Text annotations are derived from the audio filenames and represent the spoken content in each audio file.

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

Additional Information

Licensing Information

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

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/[your-username]/twi-words-speech-text-parallel}}
}

Acknowledgments

• Audio processing and alignment performed using MMS-300M-1130 Forced Aligner
• Thanks to all contributors who provided audio samples while maintaining privacy protection

Contact

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