Create hy_asr_grqaser_script.py

hy_asr_grqaser_script.py

@@ -0,0 +1,44 @@
+import os
+import pandas as pd
+from datasets import Dataset, DatasetDict, Features, Value, Audio
+
+def load_dataset_script(data_dir):
+    """
+    Load dataset script for custom audio-transcription dataset.
+
+    :param data_dir: Directory where the data and metadata.csv are stored.
+    :return: A Hugging Face Dataset object.
+    """
+    # Load metadata.csv
+    metadata = pd.read_csv(os.path.join(data_dir, "metadata.csv"))
+    
+    # Create lists for audio files and transcriptions
+    audio_files = []
+    transcriptions = []
+
+    # Iterate through the metadata and populate the lists
+    for _, row in metadata.iterrows():
+        audio_files.append({'path': os.path.join(data_dir, row['file_name'])})
+        transcriptions.append(row['transcription'])
+
+    # Define features of the dataset
+    features = Features({
+        'audio': Audio(sampling_rate=16_000),  # Adjust the sampling rate as needed
+        'sentence': Value('string')
+    })
+
+    # Create a dataset
+    dataset = Dataset.from_dict({
+        'audio': audio_files,
+        'sentence': transcriptions
+    }, features=features)
+
+    # You can split the dataset here if needed, or return as a single dataset
+    return DatasetDict({'train': dataset})
+
+
+# Example usage
+if __name__ == "__main__":
+    data_directory = "path/to/your/data"
+    dataset = load_dataset_script(data_directory)
+    print(dataset)