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--- |
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language: tr |
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datasets: |
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- common_voice |
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metrics: |
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- wer |
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tags: |
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- audio |
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- automatic-speech-recognition |
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- speech |
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license: apache-2.0 |
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model-index: |
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- name: XLSR Wav2Vec2 Turkish by Davut Emre TASAR |
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results: |
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- task: |
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name: Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Common Voice tr |
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type: common_voice |
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args: tr |
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metrics: |
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- name: Test WER |
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type: wer |
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--- |
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# wav2vec-tr-lite-AG |
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## Usage |
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The model can be used directly (without a language model) as follows: |
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```python |
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import torch |
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import torchaudio |
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from datasets import load_dataset |
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from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor |
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test_dataset = load_dataset("common_voice", "tr", split="test[:2%]") |
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processor = Wav2Vec2Processor.from_pretrained("emre/wav2vec-tr-lite-AG") |
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model = Wav2Vec2ForCTC.from_pretrained("emre/wav2vec-tr-lite-AG") |
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resampler = torchaudio.transforms.Resample(48_000, 16_000) |
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**Test Result**: 27.30 % |
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[here](https://adresgezgini.com) |
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