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Datasets:
mesolitica
/
Malaysian-STT-Whisper

Tasks:
Automatic Speech Recognition
Languages:
Malay
English
Chinese
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Malaysian-STT-Whisper / README.md
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metadata
task_categories:
  - automatic-speech-recognition
language:
  - ms
  - en
  - zh
  - ta
  - id

Malaysian STT Whisper format

Up to 15k hours annotated, we done heavy postprocessing and post-translation to improve pseudolabeled Whisper Large V3.

Also include word level timestamp.

Postprocessing

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

Post-translation

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

Dataset involved

  1. Malaysian context v1
  2. Malaysian context v2
  3. Malay audiobook
  4. Singaporean context
  5. Indonesian context
  6. Mandarin audio
  7. Tamil audio
  8. Science context
  9. Malay sarawak
  10. Scripted Malay Daily Use Speech Corpus
  11. Malay Conversational Speech Corpus
  12. Iban
  13. Malay dialects

Word level timestamp

  1. Malaysian context v1

Source code

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