metadata
language:
- en
pretty_name: imda-
IMDA National Speech Corpus (NSC) Speech-to-Text
Originally from https://www.imda.gov.sg/how-we-can-help/national-speech-corpus, this repository simply a mirror. This dataset associated with Singapore Open Data Licence, https://www.sla.gov.sg/newsroom/statistics/singapore-open-data-licence
We uploaded mp3 files and compressed using 7z,
7za x part1-mp3.7z.001
All notebooks at https://github.com/mesolitica/malaysian-dataset/tree/master/speech-to-text/imda
total lengths
- part 1, 1117.9866586978865 hours
- part 2, 1052.1777120312486 hours
- part 3, 2162.4968734548597 hours
- part 4, 2133.685638097089 hours
- part 5, 2044.5220318402826 hours
Why no HuggingFace dataset format?
We had bad experiences with HuggingFace dataset format to load huge dataset. Reading mp3 files during iteration is much more faster and efficient.