SaraSadeghi
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Update README.md
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README.md
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@@ -78,8 +78,6 @@ print(prediction[0])
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## Evaluation
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For the evaluation use the code below:
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```python
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pip install datasets
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pip install transformers
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import torch
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import torchaudio
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import librosa
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@@ -114,7 +112,12 @@ def predict(batch):
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batch["prediction"] = processor.batch_decode(logits.numpy()).text
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return batch
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dataset = load_dataset("csv", data_files={"test":"path/to/your.csv"}, delimiter=",")["test"]
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dataset = dataset.map(speech_file_to_array_fn)
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result = dataset.map(predict, batched=True, batch_size=4)
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## Evaluation
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For the evaluation use the code below:
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```python
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import torch
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import torchaudio
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import librosa
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batch["prediction"] = processor.batch_decode(logits.numpy()).text
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return batch
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dataset = load_dataset("csv", data_files={"test":"path/to/your.csv"}, delimiter=",")["test"]
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```
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| path| reference|
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| path to audio files | corresponding transcription|
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```
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dataset = dataset.map(speech_file_to_array_fn)
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result = dataset.map(predict, batched=True, batch_size=4)
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