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su_id_tts.py

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+import csv
+import os
+from pathlib import Path
+from typing import List
+
+import datasets
+
+from nusacrowd.utils import schemas
+from nusacrowd.utils.configs import NusantaraConfig
+from nusacrowd.utils.constants import (DEFAULT_NUSANTARA_VIEW_NAME,
+                                       DEFAULT_SOURCE_VIEW_NAME, Tasks)
+
+_DATASETNAME = "su_id_tts"
+_SOURCE_VIEW_NAME = DEFAULT_SOURCE_VIEW_NAME
+_UNIFIED_VIEW_NAME = DEFAULT_NUSANTARA_VIEW_NAME
+
+_LANGUAGES = ["sun"]
+_LOCAL = False
+_CITATION = """\
+@inproceedings{sodimana18_sltu,
+  author={Keshan Sodimana and Pasindu {De Silva} and Supheakmungkol Sarin and Oddur Kjartansson and Martin Jansche and Knot Pipatsrisawat and Linne Ha},
+  title={{A Step-by-Step Process for Building TTS Voices Using Open Source Data and Frameworks for Bangla, Javanese, Khmer, Nepali, Sinhala, and Sundanese}},
+  year=2018,
+  booktitle={Proc. 6th Workshop on Spoken Language Technologies for Under-Resourced Languages (SLTU 2018)},
+  pages={66--70},
+  doi={10.21437/SLTU.2018-14}
+}
+"""
+
+_DESCRIPTION = """\
+This data set contains high-quality transcribed audio data for Sundanese. The data set consists of wave files, and a TSV file. The file line_index.tsv contains a filename and the transcription of audio in the file. Each filename is prepended with a speaker identification number.
+The data set has been manually quality checked, but there might still be errors.
+This dataset was collected by Google in collaboration with Universitas Pendidikan Indonesia.
+"""
+
+_HOMEPAGE = "http://openslr.org/44/"
+
+_LICENSE = "CC BY-SA 4.0"
+
+_URLs = {
+    _DATASETNAME: {
+        "female": "https://www.openslr.org/resources/44/su_id_female.zip",
+        "male": "https://www.openslr.org/resources/44/su_id_male.zip",
+    }
+}
+
+_SUPPORTED_TASKS = [Tasks.TEXT_TO_SPEECH]
+
+_SOURCE_VERSION = "1.0.0"
+_NUSANTARA_VERSION = "1.0.0"
+
+
+class SuIdTTS(datasets.GeneratorBasedBuilder):
+    """su_id_tts contains high-quality Multi-speaker TTS data for Sundanese (SU-ID)."""
+
+    BUILDER_CONFIGS = [
+        NusantaraConfig(
+            name="su_id_tts_source",
+            version=datasets.Version(_SOURCE_VERSION),
+            description="SU_ID_TTS source schema",
+            schema="source",
+            subset_id="su_id_tts",
+        ),
+        NusantaraConfig(
+            name="su_id_tts_nusantara_sptext",
+            version=datasets.Version(_NUSANTARA_VERSION),
+            description="SU_ID_TTS Nusantara schema",
+            schema="nusantara_sptext",
+            subset_id="su_id_tts",
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = "su_id_tts_source"
+
+    def _info(self):
+        if self.config.schema == "source":
+            features = datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "speaker_id": datasets.Value("string"),
+                    "path": datasets.Value("string"),
+                    "audio": datasets.Audio(sampling_rate=16_000),
+                    "text": datasets.Value("string"),
+                    "gender": datasets.Value("string"),
+                }
+            )
+        elif self.config.schema == "nusantara_sptext":
+            features = schemas.speech_text_features
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+            task_templates=[datasets.AutomaticSpeechRecognition(audio_column="audio", transcription_column="text")],
+        )
+
+    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
+        male_path = Path(dl_manager.download_and_extract(_URLs[_DATASETNAME]["male"]))
+        female_path = Path(dl_manager.download_and_extract(_URLs[_DATASETNAME]["female"]))
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "male_filepath": male_path,
+                    "female_filepath": female_path,
+                },
+            ),
+        ]
+
+    def _generate_examples(self, male_filepath: Path, female_filepath: Path):
+
+        if self.config.schema == "source" or self.config.schema == "nusantara_sptext":
+            tsv_m = os.path.join(male_filepath, "su_id_male", "line_index.tsv")
+            tsv_f = os.path.join(female_filepath, "su_id_female", "line_index.tsv")
+
+            with open(tsv_m, "r") as file:
+                tsv_m_data = csv.reader(file, delimiter="\t")
+                for line in tsv_m_data:
+                    spk_trans_info = line[0].split("_")
+                    if self.config.schema == "source":
+                        ex = {
+                            "id": line[0],
+                            "speaker_id": spk_trans_info[0] + "_" + spk_trans_info[1],
+                            "path": os.path.join(male_filepath, "su_id_male", "wavs", "{}.wav".format(line[0])),
+                            "audio": os.path.join(male_filepath, "su_id_male", "wavs", "{}.wav".format(line[0])),
+                            "text": line[2],
+                            "gender": spk_trans_info[0][2],
+                        }
+                        yield line[0], ex
+
+                    elif self.config.schema == "nusantara_sptext":
+                        ex = {
+                            "id": line[0],
+                            "speaker_id": spk_trans_info[0] + "_" + spk_trans_info[1],
+                            "path": os.path.join(male_filepath, "su_id_male", "wavs", "{}.wav".format(line[0])),
+                            "audio": os.path.join(male_filepath, "su_id_male", "wavs", "{}.wav".format(line[0])),
+                            "text": line[2],
+                            "metadata": {
+                                "speaker_age": None,
+                                "speaker_gender": spk_trans_info[0][2],
+                            },
+                        }
+                        yield line[0], ex
+
+            with open(tsv_f, "r") as file:
+                tsv_f_data = csv.reader(file, delimiter="\t")
+                for line in tsv_f_data:
+                    spk_trans_info = line[0].split("_")
+                    if self.config.schema == "source":
+                        ex = {
+                            "id": line[0],
+                            "speaker_id": spk_trans_info[0] + "_" + spk_trans_info[1],
+                            "path": os.path.join(female_filepath, "su_id_female", "wavs", "{}.wav".format(line[0])),
+                            "audio": os.path.join(female_filepath, "su_id_female", "wavs", "{}.wav".format(line[0])),
+                            "text": line[2],
+                            "gender": spk_trans_info[0][2],
+                        }
+                        yield line[0], ex
+
+                    elif self.config.schema == "nusantara_sptext":
+                        ex = {
+                            "id": line[0],
+                            "speaker_id": spk_trans_info[0] + "_" + spk_trans_info[1],
+                            "path": os.path.join(female_filepath, "su_id_female", "wavs", "{}.wav".format(line[0])),
+                            "audio": os.path.join(female_filepath, "su_id_female", "wavs", "{}.wav".format(line[0])),
+                            "text": line[2],
+                            "metadata": {
+                                "speaker_age": None,
+                                "speaker_gender": spk_trans_info[0][2],
+                            },
+                        }
+                        yield line[0], ex
+        else:
+            raise ValueError(f"Invalid config: {self.config.name}")