readme: ---
  license: mit
  language:
  - ko
  metrics:
  - cer
  pipeline_tag: automatic-speech-recognition
  tags:
  - ksponspeech
  model-index:
  - name: cwwojin/stt_kr_conformer_ctc_small_10
    results:
    - task:
        type: automatic-speech-recognition             # Required. Example: automatic-speech-recognition
      dataset:
        type: Murple/ksponspeech          # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
        name: KsponSpeech (Korean)          # Required. A pretty name for the dataset. Example: Common Voice (French)
        split: test        # Optional. Example: test
      metrics:
        - type: cer         # Required. Example: wer. Use metric id from https://hf.co/metrics
          value: 17.83       # Required. Example: 20.90
          name: Test CER (%)         # Optional. Example: Test WER
  ---
  
  # stt_kr_conformer_ctc_small_10
  - Fine-tuned from "phtran/stt_en_conformer_ctc_small"
  - 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
  ## Training
  - 10 epochs
  ## Evaluation
  - "KsponSpeech_eval_clean", "KsponSpeech_eval_other"
  - CER : 17.83 (%)