Create new file

coraal-asr.py

@@ -0,0 +1,146 @@
+# coding=utf-8
+# Copyright 2021 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.
+""" Common Voice Dataset"""
+
+import json
+import os
+from copy import deepcopy
+import re
+import unicodedata
+from more_itertools import windowed
+import datasets
+
+_CITATION = """\
+"""
+
+_DESCRIPTION = """\
+coraalを音声認識した誤り訂正用データセット
+"""
+_HOMEPAGE = ""
+_LICENSE = ""
+
+URLS = {
+    "v1": {
+        "text": "https://huggingface.co/datasets/Padomin/coraal-asr/resolve/main/coraal-asr.tar.gz",
+    }
+}
+
+
+class coraal_asr_config(datasets.BuilderConfig):
+    def __init__(self, n_fronts=0, n_bodies=1, n_rears=0, front_prefix='front:\n', body_prefix='body:\n', rear_prefix='rear:\n', **kwargs):
+        super(coraal_asr_config, self).__init__(**kwargs)
+        self.n_fronts = n_fronts
+        self.n_bodies = n_bodies
+        self.n_rears = n_rears
+        self.front_prefix = front_prefix
+        self.body_prefix = body_prefix
+        self.rear_prefix = rear_prefix
+
+class coraal_asr(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("0.2.0")
+    BUILDER_CONFIGS = [
+        coraal_asr_config(name="v1", version=VERSION),
+    ]
+    DEFAULT_CONFIG_NAME = "v1"  # It's not mandatory to have a default configuration. Just use one if it make sense.
+    BUILDER_CONFIG_CLASS = coraal_asr_config
+
+    def _info(self):
+        feature_dict = {
+                "text": datasets.Value("string"),
+                "text_asr": datasets.Value("string"),
+                "src": datasets.Value("string"),
+                "tgt": datasets.Value("string"),
+                "id": datasets.Value("string")
+        }
+
+        features = datasets.Features(feature_dict)
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        if "v1" in self.config.name:
+            urls = deepcopy(URLS["v1"])
+            
+        dl_path = dl_manager.download_and_extract(urls)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": os.path.join(dl_path["text"], "train.jsonl"),
+                    "split": "train",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "filepath": os.path.join(dl_path["text"], "test.jsonl"),
+                    "split": "test",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "filepath": os.path.join(dl_path["text"], "validation.jsonl"),
+                    "split": "validation",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath, split):
+        """Yields examples."""
+        id_ = 0
+        with open(filepath, encoding="utf-8") as f:
+            for line in f:
+                doc = json.loads(line)
+                utterances = doc['utterances']
+                # divide text and asr
+                texts_asr = [utt['asr'] for utt in utterances]
+                texts = [utt['text'] for utt in utterances]
+                # window considering front and rear contexts
+                windowed_texts_asr = windowed([''] * self.config.n_fronts + texts_asr + [''] * self.config.n_rears, self.config.n_bodies + self.config.n_fronts + self.config.n_rears)
+                windowed_texts = windowed(texts, self.config.n_bodies)
+                
+                for text_asr, text, utt in zip(windowed_texts_asr, windowed_texts, utterances):
+                    src = ''
+                    if self.config.n_fronts > 0:
+                        src += self.config.front_prefix
+                        src += '\n'.join(text_asr[:self.config.n_fronts])
+                        src += '\n'
+                    src += self.config.body_prefix
+                    src += '\n'.join(text_asr[self.config.n_fronts:self.config.n_fronts + self.config.n_bodies])
+                    if self.config.n_rears > 0:
+                        src += '\n' + self.config.rear_prefix
+                        src += '\n'.join(text_asr[self.config.n_fronts + self.config.n_bodies:])
+                    tgt = '\n'.join(text)
+                    
+                    data = {
+                        "text": utt["text"],
+                        "text_asr": utt["asr"],
+                        'src': src,
+                        'tgt': tgt,
+                        'id': doc["id"],
+                    }
+                    
+                    yield id_, data
+                    
+                    id_ += 1