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README.md

@@ -1,22 +1,138 @@
 ---
+language:
+- tw
+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: 7107874042.356
+    num_bytes: 0
     num_examples: 21138
-  download_size: 6551669090
-  dataset_size: 7107874042.356
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+  download_size: 0
+  dataset_size: 0
+tags:
+- speech
+- twi
+- akan
+- ghana
+- african-languages
+- low-resource
+- parallel-corpus
+pretty_name: Twi Speech-Text Parallel Dataset
 ---
-# Dataset Card for "twi-speech-text-parallel-v2"
 
-[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+# Twi Speech-Text Parallel Dataset
+
+## Dataset Description
+
+This dataset contains 21138 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**: 21138 audio files > 1KB (small/corrupted files filtered out)
+- **Format**: WAV audio files with corresponding text files
+- **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 from paired text file
+
+### Data Splits
+
+The dataset contains a single training split with 21138 filtered audio-text pairs.
+
+## 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 and corresponding text files were collected from organized folder structure
+2. Text content was read from separate `.txt` files with matching filenames
+3. Files smaller than 1KB were filtered out to ensure audio quality
+4. Empty text files were excluded from the dataset
+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
+
+### Annotations
+
+Text annotations are stored in separate text files with matching filenames to the audio files, representing the spoken content in each audio recording.
+
+## 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](https://huggingface.co/MahmoudAshraf/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.