datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Malaysian-STT-Whisper
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… See the full description on the dataset page: https://huggingface.co/datasets/mesolitica/Malaysian-STT-Whisper.pseudolabel-malaysian-youtube-whisper-large-v3
Pseudolabel Malaysian Youtube videos using Whisper Large V3
Original dataset at https://huggingface.co/datasets/malaysia-ai/crawl-youtube, distributed pseudolabelled using 4x A100s
script at https://github.com/mesolitica/malaysian-dataset/tree/master/speech-to-text-semisupervised/pseudolabel-whisper
Each audio is 30 seconds.
Each audio saved in 16k sample rate.
sebut-perkataan
Sebut Perkataan
sebut-perkataan-man voice by Husein Zolkepli
tolong-sebut voice by Khalil Nooh
sebut-perkataan-woman voice by Mas Aisyah Ahmad
Recorded using low-end tech microphones.