README.md

---
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

1. **Audio Alignment**: Original audio files were processed using forced alignment to obtain word-level timestamps
2. **Trigram Segmentation**: Audio was segmented into overlapping trigrams (3-word sequences)
3. **Fallback Segmentation**: For shorter texts, bigrams or single words were created as needed
4. **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
5. **Text Processing**: Text was lowercased and cleaned of end punctuation
6. **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](https://huggingface.co/MahmoudAshraf/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](https://huggingface.co/MahmoudAshraf/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.