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import os |
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import re |
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import datasets |
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import requests |
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_DATA_URLS = ["https://sprogtek-ressources.digst.govcloud.dk/nota/Inspiration%202016%20-%202021/", |
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"https://sprogtek-ressources.digst.govcloud.dk/nota/Inspiration%202008%20-%202016/", |
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"https://sprogtek-ressources.digst.govcloud.dk/nota/Radio-TV%20program%202007%20-%202012/", |
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"https://sprogtek-ressources.digst.govcloud.dk/nota/Radio-TV%20Program%202013%20-%202015/", |
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"https://sprogtek-ressources.digst.govcloud.dk/nota/Radio-TV%20Program%202016%20-%202018/", |
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"https://sprogtek-ressources.digst.govcloud.dk/nota/Radio-TV%20Program%202019%20-%202022/" |
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] |
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_DESCRIPTION = """\ |
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Nota lyd- og tekstdata |
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Datasættet indeholder både tekst- og taledata fra udvalgte dele af Nota's lydbogsbiblotek. Datasættet består af |
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over 500 timers oplæsninger og medfølgende transkriptioner på dansk. Al lyddata er i .wav-format, mens tekstdata |
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er i .txt-format. |
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I data indgår indlæsninger af Notas eget blad "Inspiration" og "Radio/TV", som er udgivet i perioden 2007 til 2022. |
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Nota krediteres for arbejdet med at strukturere data, således at tekst og lyd stemmer overens. |
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Nota er en institution under Kulturministeriet, der gør trykte tekster tilgængelige i digitale formater til personer |
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med synshandicap og læsevanskeligheder, fx via produktion af lydbøger og oplæsning af aviser, magasiner, mv. |
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""" |
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_HOMEPAGE = "https://sprogteknologi.dk/dataset/notalyd-ogtekstdata" |
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_LICENSE = "https://creativecommons.org/publicdomain/zero/1.0/" |
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def extract_file_links(): |
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""" |
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Extracts the web locations of the zip files containing the data |
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:return: List of web urls |
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""" |
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download_paths = [] |
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download_files_regex = re.compile("<a href=\"(.+?)\">") |
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for download_root in _DATA_URLS: |
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r = requests.get(download_root) |
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all_files = download_files_regex.findall(str(r.content)) |
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all_files_filtered = filter(lambda x: x != "Readme.txt" and x != "/nota/", all_files) |
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for download_file in all_files_filtered: |
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if "INSL20210003.zip" in download_file: |
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continue |
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full_download_path = download_root + download_file |
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full_download_path = full_download_path.replace("%20", " ") |
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download_paths.append(full_download_path) |
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return download_paths |
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class NotaDanishSoundAndTextDataset(datasets.GeneratorBasedBuilder): |
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DEFAULT_CONFIG_NAME = "all" |
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def _info(self): |
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features = datasets.Features( |
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{ |
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"audio": datasets.Audio(sampling_rate=44_100), |
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"sentence": datasets.Value("string"), |
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} |
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) |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=features, |
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supervised_keys=None, |
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homepage=_HOMEPAGE, |
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license=_LICENSE, |
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) |
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def _split_generators(self, dl_manager): |
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download_urls = extract_file_links() |
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dl_path = dl_manager.download_and_extract(download_urls) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={ |
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"dl_path": dl_path, |
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}, |
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) |
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] |
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@staticmethod |
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def _extract_transcript(file_path): |
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with open(file_path, "r", encoding="utf-8") as f: |
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data = f.read() |
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return data |
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def _generate_examples(self, dl_path): |
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key = 0 |
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transcripts = {} |
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for parent_directory in dl_path: |
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parent_directory_path = os.listdir(os.path.join(dl_path, parent_directory)) |
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for sub_directory in parent_directory_path: |
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data_directory_path = os.path.join(dl_path, parent_directory, sub_directory) |
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data_files = os.listdir(data_directory_path) |
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for data_file in data_files: |
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file_type = data_file[-3:] |
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file_id = data_file[:-4] |
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if file_id not in transcripts: |
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transcripts[file_id] = {} |
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if file_type == "wav": |
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transcripts[file_id]["audio_path"] = os.path.join(data_directory_path, data_file) |
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elif file_type == "txt": |
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transcripts[file_id]["sentence"] = self._extract_transcript( |
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os.path.join(data_directory_path, data_file)) |
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for sample_id, info in transcripts.items(): |
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audio = {"path": info["audio_path"]} |
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yield key, {"audio": audio, "sentence": info["sentence"]} |
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key += 1 |
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transcripts = {} |
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