Delete app.py
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app.py
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from collections import defaultdict
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import os
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import json
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import csv
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import datasets
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import pandas as pd
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_DESCRIPTION = """
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A large-scale speech corpus for representation learning, semi-supervised learning and interpretation.
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"""
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_CITATION = """
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@inproceedings{}
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"""
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_HOMEPAGE = ""
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_LICENSE = ""
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_ASR_LANGUAGES = [
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"hy"
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]
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_ASR_ACCENTED_LANGUAGES = [
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""
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]
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_LANGUAGES = _ASR_LANGUAGES + _ASR_ACCENTED_LANGUAGES
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class HySpeech(datasets.GeneratorBasedBuilder):
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"""The VoxPopuli dataset."""
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VERSION = datasets.Version("1.1.0") # TODO: version
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DEFAULT_WRITER_BATCH_SIZE = 256
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def _info(self):
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features = datasets.Features(
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{
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"speaker_id": datasets.Value("string"),
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"audio": datasets.Audio(sampling_rate=16_000),
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"raw_text": datasets.Value("string"),
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"normalized_text": datasets.Value("string"),
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"gender": datasets.Value("string"), # TODO: ClassVar?
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"is_gold_transcript": datasets.Value("bool"),
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"accent": datasets.Value("string"),
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}
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)
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=features,
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homepage=_HOMEPAGE,
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license=_LICENSE,
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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pass
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def _generate_examples(self):
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csv_file_path = "segments_info.csv"
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df = pd.read_csv(csv_file_path)
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for idx, row in df.iterrows():
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yield idx, {
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"speaker_id": row['speaker_id'],
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"audio": row["audio_path"],
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"raw_text": row["raw_text"],
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"normalized_text": row["normalized_text"],
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"gender": row["gender"],
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"is_gold_transcript": True, # You may need to change this
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"accent": "None", # You may need to change this
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}
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