Instructions to use cwwojin/stt_kr_conformer_ctc_medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use cwwojin/stt_kr_conformer_ctc_medium with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("cwwojin/stt_kr_conformer_ctc_medium") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
stt_kr_conformer_ctc_medium
- Fine-tuned from "stt_en_conformer_ctc_medium" https://catalog.ngc.nvidia.com/orgs/nvidia/teams/nemo/models/stt_en_conformer_ctc_medium
- Trained on KsponSpeech, provided by https://aihub.or.kr/
Preprocessing
- Files converted from .pcm -> .wav
- Text - Korean phonetic transcription
- SentencePiece tokenizer (Byte-pair encoding), vocab-size = 5,000
Evaluation
- "KsponSpeech_eval_clean", "KsponSpeech_eval_other"
- Downloads last month
- 2
Evaluation results
- Test CER(%) on KsponSpeech-eval (Korean)test set self-reported11.902