First version of CrowdSpeech

CrowdSpeech.py

@@ -0,0 +1,114 @@
+# coding=utf-8
+# Copyright 2021 YANDEX LLC.
+#
+# 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.
+
+# Lint as: python3
+"""CrowdSpeech:  Benchmark Dataset for Crowdsourced Audio Transcription."""
+
+
+import json
+
+import datasets
+from datasets.tasks import Summarization
+
+
+logger = datasets.logging.get_logger(__name__)
+
+_DESCRIPTION = """\
+CrowdSpeech is a publicly available large-scale dataset of crowdsourced audio transcriptions. \
+It contains annotations for more than 50 hours of English speech transcriptions from more \
+than 1,000 crowd workers.
+"""
+
+_URL = "https://raw.githubusercontent.com/pilot7747/VoxDIY/main/data/huggingface/"
+_URLS = {
+    "train-clean": _URL + "train-clean.json",
+    "dev-clean": _URL + "dev-clean.json",
+    "dev-other": _URL + "dev-other.json",
+    "test-clean": _URL + "test-clean.json",
+    "test-other": _URL + "test-other.json",
+}
+
+
+class CrowdSpeechConfig(datasets.BuilderConfig):
+    """BuilderConfig for CrowdSpeech."""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig for CrowdSpeech.
+
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(CrowdSpeechConfig, self).__init__(**kwargs)
+
+
+class CrowdSpeech(datasets.GeneratorBasedBuilder):
+    """CrowdSpeech:  Benchmark Dataset for Crowdsourced Audio Transcription."""
+
+    BUILDER_CONFIGS = [
+        CrowdSpeechConfig(
+            name="plain_text",
+            version=datasets.Version("1.0.0", ""),
+            description="Plain text",
+        ),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "task": datasets.Value("string"),
+                    "transcriptions": datasets.Value("string"),
+                    "performers": datasets.Value("string"),
+                    "gt": datasets.Value("string"),
+                }
+            ),
+            supervised_keys=None,
+            homepage="https://github.com/pilot7747/VoxDIY/",
+            # citation=_CITATION,
+            task_templates=[
+                Summarization(
+                    text_column="transcriptions", summary_column="gt"
+                )
+            ],
+        )
+
+    def _split_generators(self, dl_manager):
+        downloaded_files = dl_manager.download_and_extract(_URLS)
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train-clean"]}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test-clean"]}),
+            datasets.SplitGenerator(name='test-other', gen_kwargs={"filepath": downloaded_files["test-other"]}),
+            datasets.SplitGenerator(name='dev-clean', gen_kwargs={"filepath": downloaded_files["dev-clean"]}),
+            datasets.SplitGenerator(name='dev-other', gen_kwargs={"filepath": downloaded_files["dev-clean"]}),
+        ]
+
+    def _generate_examples(self, filepath):
+        """This function returns the examples in the raw (text) form."""
+        logger.info("generating examples from = %s", filepath)
+        with open(filepath, encoding="utf-8") as f:
+            crowdspeech = json.load(f)
+            for audio in crowdspeech["data"]:
+                task = audio.get("task", "")
+                transcriptions = audio.get("transcriptions", "")
+                performers = audio.get("performers", "")
+                gt = audio.get("gt", "")
+
+                yield task, {
+                    "transcriptions": transcriptions,
+                    "performers": performers,
+                    "gt": gt,
+                }