SLPL
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SaraSadeghi commited on
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Update 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
@@ -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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+ |---|---|
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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)