Dataset Viewer
The dataset viewer is not available for this dataset.
Unexpected token '<', "<html>
<h"... is not valid JSON
Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Dataset Card
Overview
This dataset contains manually reviewed audio samples and their corresponding transcriptions and phoneme sequences.
It is designed for tasks in speech recognition, phoneme alignment, and analysis of pronunciation vs. orthographic transcription.
Features
| Column name | Description |
|---|---|
| audio | The raw audio signal, sampled at 44.1 kHz. |
| auto_transcription | The text output generated by an automatic speech recognition (ASR) system before manual correction. |
| correct_transcription | The manually reviewed and corrected transcription of the audio. |
| auto_phoneme | The phoneme sequence automatically generated from the ASR output. |
| correct_phoneme | The ideal phoneme sequence obtained by converting correct_transcription to phonemes according to standard rules. For example, in Arabic, a final consonant may end with sukun if it is at the end of the utterance. |
| sound_matching_phoneme | The phoneme sequence that matches what is actually pronounced in the audio, even if it differs from the orthographic norm. For example, an Arabic word that is orthographically ended with sukun may be pronounced with a final vowel (haraka) in natural speech. |
| file_name | The original file name or identifier for the audio clip. |
| phonemes_BW | The phonem representation in BW using Nawar Alhalaby |
Dataset Statistics
- Total audio length: 7,367.31 seconds (~2.05 hours)
- Total
sound_matching_phonemecharacter count: 129,951 - Total
sound_matching_phonemeword count: 14,397 - Total
correct_transcriptioncharacter count: 129,329 - Total
correct_transcriptionword count: 13,762
Notes
- Manual Review:
correct_transcriptionandcorrect_phonemewere fully reviewed and corrected by human annotators. - Usage: Ideal for evaluating ASR output quality, studying phonetic variation, and training models that account for differences between expected and actual pronunciation.
- Language-specific note: In Arabic, differences between
correct_phonemeandsound_matching_phonemeoften arise due to sentence-final pauses, vowel insertion, or pronunciation habits.
- Downloads last month
- 15