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# Copyright 2024 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""ASR Dataset for various football leagues and seasons"""
import json
import os
import datasets
_CITATION = """\
@InProceedings{huggingface:dataset,
title = {ASR Dataset for Football Leagues},
author={Your Name},
year={2024}
}
"""
_DESCRIPTION = """\
This dataset contains Automatic Speech Recognition (ASR) data for various football leagues and seasons.
The dataset includes ASR outputs from Whisper v1, v2, and v3, along with their English-translated versions.
"""
_HOMEPAGE = "https://github.com/SoccerNet/sn-echoes"
_LICENSE = "Apache License 2.0"
_URLS = {
"whisper_v1": "whisper_v1/",
"whisper_v1_en": "wisper_v1_en/",
"whisper_v2": "wisper_v2/",
"whisper_v2_en": "wisper_v2_en/",
"whisper_v3": "wisper_v3/",
}
class FootballASRDataset(datasets.GeneratorBasedBuilder):
"""ASR Dataset for various football leagues and seasons"""
VERSION = datasets.Version("1.0.0")
BUILDER_CONFIGS = [
datasets.BuilderConfig(name="whisper_v1", version=VERSION, description="Contains ASR from Whisper v1"),
datasets.BuilderConfig(name="whisper_v1_en", version=VERSION, description="English-translated datasets from Whisper v1"),
# datasets.BuilderConfig(name="whisper_v2", version=VERSION, description="Contains ASR from Whisper v2"),
# datasets.BuilderConfig(name="whisper_v2_en", version=VERSION, description="English-translated datasets from Whisper v2"),
# datasets.BuilderConfig(name="whisper_v3", version=VERSION, description="Contains ASR from Whisper v3"),
]
DEFAULT_CONFIG_NAME = "whisper_v1"
def _info(self):
features = datasets.Features(
{
"segment_index": datasets.Value("int32"),
"start_time": datasets.Value("float"),
"end_time": datasets.Value("float"),
"transcribed_text": datasets.Value("string"),
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
urls = _URLS[self.config.name]
data_dir = dl_manager.download_and_extract("https://codeload.github.com/SoccerNet/sn-echoes/zip/refs/heads/main") +"/sn-echoes-main/Dataset/"
print("data_dir", { "data_dir": os.path.join(data_dir+ urls),})
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"data_dir": os.path.join(data_dir+ urls),
},)
]
def _generate_examples(self, data_dir,):
for root, _, files in os.walk(data_dir):
for file in files:
if file.endswith(".json"):
with open(os.path.join(root, file), encoding="utf-8") as f:
data = json.load(f)
for segment_index, segment_data in data["segments"].items():
yield f"{file}_{segment_index}", {
"segment_index": segment_index,
"start_time": segment_data[0],
"end_time": segment_data[1],
"transcribed_text": segment_data[2],
}
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