Datasets:

---

obadx

/

recitation-segmentation-augmented

like 0

This PR significantly enhances the dataset card for the Recitation Segmentations Dataset by incorporating comprehensive information for better discoverability and usability.

Key changes include:

• Metadata:
  • Added task_categories: automatic-speech-recognition to align with the paper's focus on ASR-based pronunciation error detection.
  • Included language: ar as the dataset consists of Holy Quranic recitations in Arabic.
  • Set license: cc-by-nc-4.0 to accurately reflect the license of the underlying audio data from everyayah.com, as referenced in the GitHub repository.
  • Added relevant tags such as quran, arabic, speech-segmentation, and audio for improved searchability.
• Paper/Project/Code Links: Prominently featured links to the associated research paper, the project page, and the GitHub repository.
• Introduction: Added a concise introduction summarizing the paper's abstract to provide immediate context for the dataset.
• Results: Included the model's performance metrics from the GitHub README, showcasing the dataset's utility.
• Sample Usage: Provided a Python code snippet, directly sourced from the GitHub README, demonstrating how to use the recitations-segmenter library which is built upon this dataset. Installation prerequisites are also included to guide users.
• License Statement: Explicitly stated the dataset's license within the Markdown content.

These updates provide a more informative and accessible resource for the Hugging Face community.