Add basic dataset script

the-mc-speech-dataset.py

@@ -0,0 +1,67 @@
+# coding=utf-8
+
+import datasets
+
+
+_DESCRIPTION = """\
+This is public domain speech dataset consisting of 24018 short audio clips of a single speaker
+reading sentences in Polish. A transcription is provided for each clip. Clips have total length of
+more than 22 hours.
+Texts are in public domain. The audio was recorded in 2021-22 as a part of my master's thesis and
+is in public domain.
+"""
+_HOMEPAGE = "https://github.com/czyzi0/the-mc-speech-dataset"
+_CITATION = """\
+@masterthesis{mcspeech,
+  title={Analiza porównawcza korpusów nagrań mowy dla celów syntezy mowy w języku polskim},
+  author={Czyżnikiewicz, Mateusz},
+  year={2022},
+  month={December},
+  school={Warsaw University of Technology},
+  type={Master's thesis},
+  doi={10.13140/RG.2.2.26293.24800},
+  note={Available at \url{http://dx.doi.org/10.13140/RG.2.2.26293.24800}},
+}
+"""
+_LICENSE = "CC0 1.0"
+
+
+
+class MCSpeech(datasets.GeneratorBasedBuilder):
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "transcript": datasets.Value("string"),
+                },
+            ),
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+            license=_LICENSE,
+        )
+
+    def _split_generators(self, dl_manager):
+        transcripts_path = dl_manager.download_and_extract(
+            "https://huggingface.co/datasets/czyzi0/the-mc-speech-dataset/raw/main/transcripts.tsv"
+        )
+        return [
+            datasets.SplitGenerator(
+                name="train",
+                gen_kwargs={"transcripts_path": transcripts_path}
+            )
+        ]
+
+    def _generate_examples(self, transcipts_path):
+        with open(transcripts_path, "r") as fh:
+            header = next(fh).strip().split("\t")
+            for item_idx, line in enumerate(fh):
+                line = line.strip().split("\t")
+                item = {
+                    "id": line[header.index("id")],
+                    "transcript": line[header.index("transcript")],
+                }
+                yield item_idx, item