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--- |
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language: kr |
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datasets: |
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- aihub 자유대화 음성(노인남녀) |
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tags: |
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- automatic-speech-recognition |
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license: apache-2.0 |
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--- |
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# wav2vec2-xlsr-korean-senior |
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Futher fine-tuned [fleek/wav2vec-large-xlsr-korean](https://huggingface.co/fleek/wav2vec-large-xlsr-korean) using the [AIhub 자유대화 음성(노인남녀)](https://aihub.or.kr/aidata/30704). |
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- Total train data size: 808,642 |
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- Total vaild data size: 159,970 |
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When using this model, make sure that your speech input is sampled at 16kHz. |
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The script used for training can be found here: https://github.com/hyyoka/wav2vec2-korean-senior |
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### Inference |
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``` py |
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import torchaudio |
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from transformers import Wav2Vec2Processor, Wav2Vec2ForCTC |
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import re |
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def clean_up(transcription): |
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hangul = re.compile('[^ ㄱ-ㅣ가-힣]+') |
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result = hangul.sub('', transcription) |
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return result |
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model_name "hyyoka/wav2vec2-xlsr-korean-senior" |
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processor = Wav2Vec2Processor.from_pretrained(model_name) |
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model = Wav2Vec2ForCTC.from_pretrained(model_name) |
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speech_array, sampling_rate = torchaudio.load(wav_file) |
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feat = processor(speech_array[0], |
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sampling_rate=16000, |
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padding=True, |
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max_length=800000, |
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truncation=True, |
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return_attention_mask=True, |
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return_tensors="pt", |
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pad_token_id=49 |
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) |
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input = {'input_values': feat['input_values'],'attention_mask':feat['attention_mask']} |
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outputs = model(**input, output_attentions=True) |
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logits = outputs.logits |
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predicted_ids = logits.argmax(axis=-1) |
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transcription = processor.decode(predicted_ids[0]) |
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stt_result = clean_up(transcription) |
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``` |
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