## import os import pandas as pd from datasets import GeneratorBasedBuilder, DatasetInfo, SplitGenerator, Split, Features, Value, Audio, Version class HyAsrGrqaser(GeneratorBasedBuilder): """Armenian Audio-Transcription Dataset""" VERSION = Version("1.0.0") def _info(self): return DatasetInfo( description="This dataset contains Armenian speech and transcriptions.", features=Features({ 'audio': Audio(sampling_rate=16_000), # Adjust the sampling rate as needed 'sentence': Value('string') }), supervised_keys=("audio", "sentence"), ) def _split_generators(self, dl_manager): """Returns SplitGenerators.""" # Assuming the script is in the root of the project structure data_dir = os.path.dirname(__file__) metadata_path = os.path.join(os.path.dirname(__file__), "metadata.csv") return [ SplitGenerator( name=Split.TRAIN, gen_kwargs={"data_dir": data_dir, "metadata_path": metadata_path} ), ] def _generate_examples(self, data_dir, metadata_path): """Yields examples.""" # Load metadata.csv metadata = pd.read_csv(metadata_path) # Generate examples for idx, row in metadata.iterrows(): file_path = os.path.join(data_dir, row['file_name']) transcription_path = os.path.join(data_dir, row['transcription_file']) with open(transcription_path, 'r') as f: transcription = f.read().strip() yield idx, { 'audio': {'path': file_path}, 'sentence': transcription } # Testing the dataset locally # if __name__ == "__main__": # from datasets import load_dataset # dataset = load_dataset("C:\\Projects\\aeneas\\hy_asr_grqaser\\hy_asr_grqaser.py") # print(dataset["train"][0]) ## from datasets import load_dataset dataset = load_dataset("aburnazy/hy_asr_grqaser") print(dataset)