add script

clarinpl_studio.py

@@ -0,0 +1,161 @@
+# coding=utf-8
+# Copyright 2021 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
+# Copyright 2021 Jim O'Regan
+#
+# 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
+"""ClarinPL Studio automatic speech recognition dataset."""
+
+import os
+import glob
+
+import datasets
+
+
+_CITATION = """\
+@article{korvzinek2017polish,
+  title={Polish read speech corpus for speech tools and services},
+  author={Kor{\v{z}}inek, Danijel and Marasek, Krzysztof and Brocki, {\L}ukasz and Wo{\l}k, Krzysztof},
+  journal={arXiv preprint arXiv:1706.00245},
+  year={2017}
+}
+"""
+
+_DESCRIPTION = """\
+The corpus consists of 317 speakers recorded in 554
+sessions, where each session consists of 20 read sentences and 10 phonetically rich words. The size of
+the audio portion of the corpus amounts to around 56 hours, with transcriptions containing 356674 words
+from a vocabulary of size 46361.
+
+Note that in order to limit the required storage for preparing this dataset, the audio
+is stored in the .wav format and is not converted to a float32 array. To convert the audio
+file to a float32 array, please make use of the `.map()` function as follows:
+
+```python
+import soundfile as sf
+
+def map_to_array(batch):
+    speech_array, _ = sf.read(batch["file"])
+    batch["speech"] = speech_array
+    return batch
+
+dataset = dataset.map(map_to_array, remove_columns=["file"])
+```
+"""
+
+_URL = "https://mowa.clarin-pl.eu/"
+_DS_URL = "http://mowa.clarin-pl.eu/korpusy/audio.tar.gz"
+_TRAIN_URL = "https://raw.githubusercontent.com/danijel3/ClarinStudioKaldi/master/local_clarin/train.sessions"
+_TEST_URL = "https://raw.githubusercontent.com/danijel3/ClarinStudioKaldi/master/local_clarin/test.sessions"
+_VALID_URL = "https://raw.githubusercontent.com/danijel3/ClarinStudioKaldi/master/local_clarin/dev.sessions"
+
+class ClarinPLStudioASRConfig(datasets.BuilderConfig):
+    """BuilderConfig for ClarinPLStudioASR."""
+
+    def __init__(self, **kwargs):
+        """
+        Args:
+          data_dir: `string`, the path to the folder containing the files in the
+            downloaded .tar
+          citation: `string`, citation for the data set
+          url: `string`, url for information about the data set
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(ClarinPLStudioASRConfig, self).__init__(version=datasets.Version("2.1.0", ""), **kwargs)
+
+
+class ClarinPLStudio(datasets.GeneratorBasedBuilder):
+    """ClarinPL Studio dataset."""
+
+    BUILDER_CONFIGS = [
+        ClarinPLStudioASRConfig(name="clean", description="'Clean' speech."),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "file": datasets.Value("string"),
+                    "text": datasets.Value("string"),
+                    "speaker_id": datasets.Value("string"),
+                    "id": datasets.Value("string"),
+                }
+            ),
+            supervised_keys=("file", "text"),
+            homepage=_URL,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        def get_sessions(path):
+          sessions = []
+          with open(path, 'r') as f:
+            for line in f:
+              sessions.append(line.strip())
+            return sessions
+        archive_path = dl_manager.download_and_extract(_DS_URL)
+        train_sessions_path = dl_manager.download(_TRAIN_URL)
+        test_sessions_path = dl_manager.download(_TEST_URL)
+        valid_sessions_path = dl_manager.download(_VALID_URL)
+
+        train_sessions = get_sessions(train_sessions_path)
+        test_sessions = get_sessions(test_sessions_path)
+        valid_sessions = get_sessions(valid_sessions_path)
+
+        archive_path = os.path.join(archive_path, "audio")
+        return [
+            datasets.SplitGenerator(name="train", gen_kwargs={
+                "archive_path": archive_path,
+                "sessions": train_sessions
+                }),
+            datasets.SplitGenerator(name="test", gen_kwargs={
+                "archive_path": archive_path,
+                "sessions": test_sessions
+                }),
+            datasets.SplitGenerator(name="valid", gen_kwargs={
+                "archive_path": archive_path,
+                "sessions": valid_sessions
+                }),
+        ]
+
+    def _generate_examples(self, archive_path, sessions):
+        """Generate examples from a ClarinPL Studio archive_path."""
+        def get_single_line(path):
+          lines = []
+          with open(path, 'r', encoding="utf-8") as f:
+            for line in f:
+              line = line.strip()
+              lines.append(line)
+          assert(len(lines) == 1)
+          return lines[0]
+        for session in sessions:
+          session_path = os.path.join(archive_path, session)
+          speaker = get_single_line(os.path.join(session_path, "spk.txt"))
+          text_glob = os.path.join(session_path, "*.txt")
+          for text_file in sorted(glob.glob(text_glob)):
+            if text_file.endswith("spk.txt"):
+              continue
+            basename = os.path.basename(text_file)
+            basename = basename.replace('.txt', '')
+            key = f'{session}_{basename}'
+            text = get_single_line(text_file)
+            audio = text_file.replace('.txt', '.wav')
+            example = {
+                "id": key,
+                "speaker_id": speaker,
+                "file": audio,
+                "text": text,
+            }
+            yield key, example