metadata

language:
  - ny
license: cc-by-4.0
task_categories:
  - automatic-speech-recognition
  - text-to-speech
task_ids:
  - keyword-spotting
multilinguality:
  - monolingual
size_categories:
  - 1K<n<10K
modalities:
  - audio
  - text
dataset_info:
  features:
    - name: audio
      dtype: audio
    - name: text
      dtype: string
  config_name: default
  splits:
    - name: train
      num_bytes: 0
      num_examples: 132549
  download_size: 0
  dataset_size: 0
tags:
  - speech
  - chichewa
  - akan
  - ghana
  - african-languages
  - low-resource
  - parallel-corpus
  - trigrams
  - n-grams
pretty_name: Chichewa Trigrams Speech-Text Parallel Dataset

Chichewa Trigrams Speech-Text Parallel Dataset

Dataset Description

This dataset contains 132549 parallel speech-text pairs for Chichewa, a language spoken primarily in Malawi. The dataset consists of audio recordings of trigram segments (3-word sequences) paired with their corresponding text transcriptions, making it suitable for automatic speech recognition (ASR) and text-to-speech (TTS) tasks.

Dataset Summary

Language: Chichewa - ny
Task: Speech Recognition, Text-to-Speech
Size: 132549 trigram audio segments > 1KB (small/corrupted files filtered out)
Format: WAV audio files with corresponding trigram text labels
Segment Type: Primarily trigrams (3-word sequences), with some bigrams and single words as fallbacks
Modalities: Audio + Text

Supported Tasks

Automatic Speech Recognition (ASR): Train models to convert Chichewa speech to text
Text-to-Speech (TTS): Use parallel data for TTS model development
Keyword Spotting: Identify specific Chichewa word sequences in audio
N-gram Language Modeling: Study Chichewa trigram patterns
Phonetic Analysis: Study Chichewa pronunciation patterns in context

Dataset Structure

Data Fields

audio: Audio file in WAV format containing a trigram segment
text: Corresponding text transcription (typically 3 words, sometimes 2 or 1 for shorter segments)

Data Splits

The dataset contains a single training split with 132549 filtered trigram audio segments.

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

Audio Alignment: Original audio files were processed using forced alignment to obtain word-level timestamps
Trigram Segmentation: Audio was segmented into overlapping trigrams (3-word sequences)
Fallback Segmentation: For shorter texts, bigrams or single words were created as needed
Quality Filtering:
- Segments longer than 30 seconds were excluded
- Segments shorter than 0.1 seconds were excluded
- Files smaller than 1KB were filtered out to ensure audio quality
Text Processing: Text was lowercased and cleaned of end punctuation
Unique Naming: Each segment received a unique sequential filename (trigram_XXXXXX.wav)

Alignment Technology

Audio processing and word-level alignment performed using the MMS-300M-1130 Forced Aligner tool, which provides accurate timestamp information for creating precise trigram segments.

Annotations

Text annotations represent the spoken content in each trigram audio segment, with text processing applied for consistency:

Lowercased for uniformity
End punctuation removed
Spaces normalized

Considerations for Using the Data

Social Impact of Dataset

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

Language technology development for underrepresented languages
Educational resources for Chichewa language learning
Cultural preservation through digital archives
N-gram based language modeling research

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 segments
Trigram distribution may not be representative of natural Chichewa language patterns
Some segments may contain overlapping content due to the sliding window approach

Other Known Limitations

Segment-level rather than full sentence context
Potential audio quality variations benyeen segments
Regional dialect representation may be uneven
Variable segment lengths (primarily 3 words, but includes 2-word and 1-word segments)

Additional Information

Dataset Statistics

Primary Content: Trigram segments (3-word sequences)
Fallback Content: Bigram segments (2-word sequences) and single words
Segment Duration: 0.1 to 30 seconds
Minimum File Size: 1KB after processing

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{chichewa_trigrams_parallel_2025,
  title={Chichewa Trigrams Speech-Text Parallel Dataset},
  year={2025},
  publisher={Hugging Face},
  howpublished={\url{https://huggingface.co/datasets/michsethowusu/chichewa-trigrams-speech-text-parallel}}
}

Acknowledgments

Audio processing and alignment performed using MMS-300M-1130 Forced Aligner
Forced alignment and trigram segmentation using CTC forced alignment techniques
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.