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README.md
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---
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dataset_info:
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features:
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- name: audio
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dtype: audio
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- name: text
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dtype: string
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splits:
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- name: train
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num_bytes:
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num_examples: 23286
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download_size:
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dataset_size:
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---
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# Dataset Card for "vai-speech-text-parallel"
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---
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language:
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- vai
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license: cc-by-4.0
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task_categories:
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- automatic-speech-recognition
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- text-to-speech
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task_ids:
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- keyword-spotting
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multilinguality:
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- monolingual
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size_categories:
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- 1K<n<10K
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modalities:
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- audio
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- text
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dataset_info:
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features:
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- name: audio
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dtype: audio
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- name: text
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dtype: string
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config_name: default
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splits:
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- name: train
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num_bytes: 0
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num_examples: 23286
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download_size: 0
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dataset_size: 0
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tags:
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- speech
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- vai
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- liberia
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- african-languages
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- low-resource
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- parallel-corpus
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pretty_name: Vai Speech-Text Parallel Dataset
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---
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# Vai Speech-Text Parallel Dataset
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## Dataset Description
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This dataset contains 23286 parallel speech-text pairs for Vai, 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.
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### Dataset Summary
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- **Language**: Vai - `vai`
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- **Task**: Speech Recognition, Text-to-Speech
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- **Size**: 23286 audio files > 1KB (small/corrupted files filtered out)
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- **Format**: WAV audio files with corresponding text files
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- **Modalities**: Audio + Text
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### Supported Tasks
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- **Automatic Speech Recognition (ASR)**: Train models to convert Vai speech to text
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- **Text-to-Speech (TTS)**: Use parallel data for TTS model development
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- **Keyword Spotting**: Identify specific Vai words in audio
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- **Phonetic Analysis**: Study Vai pronunciation patterns
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## Dataset Structure
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### Data Fields
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- `audio`: Audio file in WAV format
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- `text`: Corresponding text transcription from paired text file
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### Data Splits
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The dataset contains a single training split with 23286 filtered audio-text pairs.
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## Dataset Creation
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### Source Data
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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.
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### Data Processing
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1. Audio files and corresponding text files were collected from organized folder structure
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2. Text content was read from separate `.txt` files with matching filenames
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3. Files smaller than 1KB were filtered out to ensure audio quality
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4. Empty text files were excluded from the dataset
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5. Audio was processed using the [MMS-300M-1130 Forced Aligner](https://huggingface.co/MahmoudAshraf/mms-300m-1130-forced-aligner) tool for alignment and quality assurance
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### Annotations
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Text annotations are stored in separate text files with matching filenames to the audio files, representing the spoken content in each audio recording.
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## Considerations for Using the Data
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### Social Impact of Dataset
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This dataset contributes to the preservation and digital representation of Vai, supporting:
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- Language technology development for underrepresented languages
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- Educational resources for Vai language learning
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- Cultural preservation through digital archives
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### Discussion of Biases
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- The dataset may reflect the pronunciation patterns and dialects of specific regions or speakers
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- Audio quality and recording conditions may vary across samples
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- The vocabulary is limited to the words present in the collected samples
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### Other Known Limitations
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- Limited vocabulary scope (word-level rather than sentence-level)
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- Potential audio quality variations
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- Regional dialect representation may be uneven
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## Additional Information
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### Licensing Information
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This dataset is released under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
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### Acknowledgments
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- Audio processing and alignment performed using [MMS-300M-1130 Forced Aligner](https://huggingface.co/MahmoudAshraf/mms-300m-1130-forced-aligner)
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- The original audio is produced by The Bible Society of Liberia in partnership with Davar Audio Bibles
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### Citation Information
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If you use this dataset in your research, please cite:
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```
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@dataset{vai_words_parallel_2025,
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title={Vai Words Speech-Text Parallel Dataset},
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year={2025},
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publisher={Hugging Face},
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howpublished={\url{https://huggingface.co/datasets/[your-username]/vai-speech-text-parallel}}
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}
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```
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### Contact
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For questions or concerns about this dataset, please open an issue in the dataset repository.
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