metadata

task_categories:
  - automatic-speech-recognition
language:
  - ms
  - en
  - zh
  - ta
  - id

Malaysian STT Whisper format

Heavy postprocessing and post-translation to improve pseudolabeled Whisper Large V3. Also include word level timestamp.

Postprocessing

Check repetitive trigrams.
Verify Voice Activity using Silero-VAD.
Verify scores using Force Alignment.

Post-translation

We use mesolitica/nanot5-base-malaysian-translation-v2.1.

Dataset involved

Malaysian context v2
Singaporean context
Indonesian context
Mandarin audio
Tamil audio
Science context
Malay sarawak
Scripted Malay Daily Use Speech Corpus
Malay Conversational Speech Corpus
Iban

how to prepare the dataset

huggingface-cli download --repo-type dataset \
--include '*.zip' \
--local-dir './' \
--max-workers 20 \
mesolitica/Malaysian-STT-Whisper

wget https://gist.githubusercontent.com/huseinzol05/2e26de4f3b29d99e993b349864ab6c10/raw/9b2251f3ff958770215d70c8d82d311f82791b78/unzip.py
python3 unzip.py

Source code

Source code at https://github.com/mesolitica/malaysian-dataset/tree/master/speech-to-text-semisupervised/distilled-malaysian-whisper