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---
license: cc-by-4.0
language:
- en
---
# Dataset Card for youtube-commons-asr-eval
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Additional Information](#additional-information)
- [Licensing Information](#licensing-information)
### Dataset Summary
This evaluation dataset is created from a subset of Youtube-Commons [PleIAs/YouTube-Commons] by selecting English YouTube videos and corresponding english subtitle.
### Supported Tasks and Leaderboards
This dataset will be primarily useful for automatic speech recognition evaluation tasks such as hf-audio/open_asr_leaderboard.
### Languages
This subset is for English language evaluations.
## Dataset Structure
The dataset consists of 94 video links, transcriptions, and normalized transcriptions (around 38 hours) of age-appropriate audios with a minimum word count of 300. With a normal speaking rate of 2.5 words per second, this corresponds to a minimum duration of 2 minutes. Minimum duration of the dataset is 128 seconds and maximum is 02:08 hours. The average duration per file is a little over 24 minutes and the standard deviation is 25 minutes. The notable variability in audio duration, as indicated by the standard deviation, mirrors typical real-time environments.
### Data Fields
Each row in the JSON file has link (link to the youtube video), text (transcription), norm_text (normalized transcription) and duration (duration of the video) fields.
### Data Splits
Evaluation data
## Dataset Creation
Normalization is done via EnglishTextNormalizer from open_asr_eval [https://github.com/huggingface/open_asr_leaderboard/blob/main/normalizer/normalizer.py]
The dataset is created by selecting the first 100 files from Youtube-Commons, with a minimum of 300 transcription words and age-appropriate content. Three files are manually removed owing to high errors in the transcription observed in visual inspection and also verified with high WER on different ASR implementations.
### Licensing Information
All the transcripts are part of a video shared under a CC-By license on YouTube. All the licensing terms are the same as the original dataset [PleIAs/YouTube-Commons].
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