|
--- |
|
annotations_creators: |
|
- no-annotation |
|
language: |
|
- en |
|
language_creators: |
|
- found |
|
license: |
|
- afl-3.0 |
|
multilinguality: |
|
- monolingual |
|
pretty_name: Youtube Transcriptions |
|
size_categories: |
|
- 10K<n<100K |
|
source_datasets: |
|
- original |
|
tags: |
|
- youtube |
|
- technical |
|
- speech to text |
|
- speech |
|
- video |
|
- video search |
|
- audio |
|
- audio search |
|
task_categories: |
|
- conversational |
|
- question-answering |
|
- text-retrieval |
|
- visual-question-answering |
|
task_ids: |
|
- open-domain-qa |
|
- extractive-qa |
|
- document-retrieval |
|
- visual-question-answering |
|
--- |
|
|
|
The YouTube transcriptions dataset contains technical tutorials (currently only from [YouTube.com/c/JamesBriggs](https://www.youtube.com/c/jamesbriggs)) transcribed using OpenAI's Whisper (large). Each row represents roughly a sentence-length chunk of text alongside the video URL and timestamp. |
