# coding=utf-8 # Copyright 2021 The HuggingFace Datasets Authors and the current dataset script contributor. # # 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. """ OpenSLR Dataset""" from __future__ import absolute_import, division, print_function import os import re from pathlib import Path import datasets from datasets.tasks import AutomaticSpeechRecognition _DATA_URL = "https://openslr.org/resources/{}" _CITATION = """\ SLR32: @inproceedings{van-niekerk-etal-2017, title = {{Rapid development of TTS corpora for four South African languages}}, author = {Daniel van Niekerk and Charl van Heerden and Marelie Davel and Neil Kleynhans and Oddur Kjartansson and Martin Jansche and Linne Ha}, booktitle = {Proc. Interspeech 2017}, pages = {2178--2182}, address = {Stockholm, Sweden}, month = aug, year = {2017}, URL = {http://dx.doi.org/10.21437/Interspeech.2017-1139} } SLR35, SLR36, SLR52, SLR53, SLR54: @inproceedings{kjartansson-etal-sltu2018, title = {{Crowd-Sourced Speech Corpora for Javanese, Sundanese, Sinhala, Nepali, and Bangladeshi Bengali}}, author = {Oddur Kjartansson and Supheakmungkol Sarin and Knot Pipatsrisawat and Martin Jansche and Linne Ha}, booktitle = {Proc. The 6th Intl. Workshop on Spoken Language Technologies for Under-Resourced Languages (SLTU)}, year = {2018}, address = {Gurugram, India}, month = aug, pages = {52--55}, URL = {https://dx.doi.org/10.21437/SLTU.2018-11}, } SLR41, SLR42, SLR43, SLR44: @inproceedings{kjartansson-etal-tts-sltu2018, title = {{A Step-by-Step Process for Building TTS Voices Using Open Source Data and Framework for Bangla, Javanese, Khmer, Nepali, Sinhala, and Sundanese}}, author = {Keshan Sodimana and Knot Pipatsrisawat and Linne Ha and Martin Jansche and Oddur Kjartansson and Pasindu De Silva and Supheakmungkol Sarin}, booktitle = {Proc. The 6th Intl. Workshop on Spoken Language Technologies for Under-Resourced Languages (SLTU)}, year = {2018}, address = {Gurugram, India}, month = aug, pages = {66--70}, URL = {https://dx.doi.org/10.21437/SLTU.2018-14} } SLR63, SLR64, SLR65, SLR66, SLR78, SLR79: @inproceedings{he-etal-2020-open, title = {{Open-source Multi-speaker Speech Corpora for Building Gujarati, Kannada, Malayalam, Marathi, Tamil and Telugu Speech Synthesis Systems}}, author = {He, Fei and Chu, Shan-Hui Cathy and Kjartansson, Oddur and Rivera, Clara and Katanova, Anna and Gutkin, Alexander and Demirsahin, Isin and Johny, Cibu and Jansche, Martin and Sarin, Supheakmungkol and Pipatsrisawat, Knot}, booktitle = {Proceedings of The 12th Language Resources and Evaluation Conference (LREC)}, month = may, year = {2020}, address = {Marseille, France}, publisher = {European Language Resources Association (ELRA)}, pages = {6494--6503}, url = {https://www.aclweb.org/anthology/2020.lrec-1.800}, ISBN = "{979-10-95546-34-4}, } SLR69, SLR76, SLR77: @inproceedings{kjartansson-etal-2020-open, title = {{Open-Source High Quality Speech Datasets for Basque, Catalan and Galician}}, author = {Kjartansson, Oddur and Gutkin, Alexander and Butryna, Alena and Demirsahin, Isin and Rivera, Clara}, booktitle = {Proceedings of the 1st Joint Workshop on Spoken Language Technologies for Under-resourced languages (SLTU) and Collaboration and Computing for Under-Resourced Languages (CCURL)}, year = {2020}, pages = {21--27}, month = may, address = {Marseille, France}, publisher = {European Language Resources association (ELRA)}, url = {https://www.aclweb.org/anthology/2020.sltu-1.3}, ISBN = {979-10-95546-35-1}, } SLR71, SLR71, SLR72, SLR73, SLR74, SLR75: @inproceedings{guevara-rukoz-etal-2020-crowdsourcing, title = {{Crowdsourcing Latin American Spanish for Low-Resource Text-to-Speech}}, author = {Guevara-Rukoz, Adriana and Demirsahin, Isin and He, Fei and Chu, Shan-Hui Cathy and Sarin, Supheakmungkol and Pipatsrisawat, Knot and Gutkin, Alexander and Butryna, Alena and Kjartansson, Oddur}, booktitle = {Proceedings of The 12th Language Resources and Evaluation Conference (LREC)}, year = {2020}, month = may, address = {Marseille, France}, publisher = {European Language Resources Association (ELRA)}, url = {https://www.aclweb.org/anthology/2020.lrec-1.801}, pages = {6504--6513}, ISBN = {979-10-95546-34-4}, } SLR80 @inproceedings{oo-etal-2020-burmese, title = {{Burmese Speech Corpus, Finite-State Text Normalization and Pronunciation Grammars with an Application to Text-to-Speech}}, author = {Oo, Yin May and Wattanavekin, Theeraphol and Li, Chenfang and De Silva, Pasindu and Sarin, Supheakmungkol and Pipatsrisawat, Knot and Jansche, Martin and Kjartansson, Oddur and Gutkin, Alexander}, booktitle = {Proceedings of The 12th Language Resources and Evaluation Conference (LREC)}, month = may, year = {2020}, pages = "6328--6339", address = {Marseille, France}, publisher = {European Language Resources Association (ELRA)}, url = {https://www.aclweb.org/anthology/2020.lrec-1.777}, ISBN = {979-10-95546-34-4}, } SLR86 @inproceedings{gutkin-et-al-yoruba2020, title = {{Developing an Open-Source Corpus of Yoruba Speech}}, author = {Alexander Gutkin and Işın Demirşahin and Oddur Kjartansson and Clara Rivera and Kọ́lá Túbọ̀sún}, booktitle = {Proceedings of Interspeech 2020}, pages = {404--408}, month = {October}, year = {2020}, address = {Shanghai, China}, publisher = {International Speech and Communication Association (ISCA)}, doi = {10.21437/Interspeech.2020-1096}, url = {https://dx.doi.org/10.21437/Interspeech.2020-1096}, } """ _DESCRIPTION = """\ OpenSLR is a site devoted to hosting speech and language resources, such as training corpora for speech recognition, and software related to speech recognition. We intend to be a convenient place for anyone to put resources that they have created, so that they can be downloaded publicly. """ _HOMEPAGE = "https://openslr.org/" _LICENSE = "" _RESOURCES = { "SLR32": { "Language": "South African", "LongName": "High quality TTS data for four South African languages (af, st, tn, xh)", "Category": "Speech", "Summary": "Multi-speaker TTS data for four South African languages, Afrikaans, Sesotho, " "Setswana and isiXhosa.", "Files": ["af_za.tar.gz", "st_za.tar.gz", "tn_za.tar.gz", "xh_za.tar.gz"], "IndexFiles": [ "https://s3.amazonaws.com/datasets.huggingface.co/openslr/SLR32/af_za/line_index.tsv", "https://s3.amazonaws.com/datasets.huggingface.co/openslr/SLR32/st_za/line_index.tsv", "https://s3.amazonaws.com/datasets.huggingface.co/openslr/SLR32/tn_za/line_index.tsv", "https://s3.amazonaws.com/datasets.huggingface.co/openslr/SLR32/xh_za/line_index.tsv", ], "DataDirs": ["af_za/za/afr/wavs", "st_za/za/sso/wavs", "tn_za/za/tsn/wavs", "xh_za/za/xho/wavs"], }, "SLR35": { "Language": "Javanese", "LongName": "Large Javanese ASR training data set", "Category": "Speech", "Summary": "Javanese ASR training data set containing ~185K utterances", "Files": [ "asr_javanese_0.zip", "asr_javanese_1.zip", "asr_javanese_2.zip", "asr_javanese_3.zip", "asr_javanese_4.zip", "asr_javanese_5.zip", "asr_javanese_6.zip", "asr_javanese_7.zip", "asr_javanese_8.zip", "asr_javanese_9.zip", "asr_javanese_a.zip", "asr_javanese_b.zip", "asr_javanese_c.zip", "asr_javanese_d.zip", "asr_javanese_e.zip", "asr_javanese_f.zip", ], "IndexFiles": ["asr_javanese/utt_spk_text.tsv"] * 16, "DataDirs": ["asr_javanese/data"] * 16, }, "SLR36": { "Language": "Sundanese", "LongName": "Large Sundanese ASR training data set", "Category": "Speech", "Summary": "Sundanese ASR training data set containing ~220K utterances", "Files": [ "asr_sundanese_0.zip", "asr_sundanese_1.zip", "asr_sundanese_2.zip", "asr_sundanese_3.zip", "asr_sundanese_4.zip", "asr_sundanese_5.zip", "asr_sundanese_6.zip", "asr_sundanese_7.zip", "asr_sundanese_8.zip", "asr_sundanese_9.zip", "asr_sundanese_a.zip", "asr_sundanese_b.zip", "asr_sundanese_c.zip", "asr_sundanese_d.zip", "asr_sundanese_e.zip", "asr_sundanese_f.zip", ], "IndexFiles": ["asr_sundanese/utt_spk_text.tsv"] * 16, "DataDirs": ["asr_sundanese/data"] * 16, }, "SLR41": { "Language": "Javanese", "LongName": "High quality TTS data for Javanese", "Category": "Speech", "Summary": "Multi-speaker TTS data for Javanese (jv-ID)", "Files": ["jv_id_female.zip", "jv_id_male.zip"], "IndexFiles": ["jv_id_female/line_index.tsv", "jv_id_male/line_index.tsv"], "DataDirs": ["jv_id_female/wavs", "jv_id_male/wavs"], }, "SLR42": { "Language": "Khmer", "LongName": "High quality TTS data for Khmer", "Category": "Speech", "Summary": "Multi-speaker TTS data for Khmer (km-KH)", "Files": ["km_kh_male.zip"], "IndexFiles": ["km_kh_male/line_index.tsv"], "DataDirs": ["km_kh_male/wavs"], }, "SLR43": { "Language": "Nepali", "LongName": "High quality TTS data for Nepali", "Category": "Speech", "Summary": "Multi-speaker TTS data for Nepali (ne-NP)", "Files": ["ne_np_female.zip"], "IndexFiles": ["ne_np_female/line_index.tsv"], "DataDirs": ["ne_np_female/wavs"], }, "SLR44": { "Language": "Sundanese", "LongName": "High quality TTS data for Sundanese", "Category": "Speech", "Summary": "Multi-speaker TTS data for Javanese Sundanese (su-ID)", "Files": ["su_id_female.zip", "su_id_male.zip"], "IndexFiles": ["su_id_female/line_index.tsv", "su_id_male/line_index.tsv"], "DataDirs": ["su_id_female/wavs", "su_id_male/wavs"], }, "SLR52": { "Language": "Sinhala", "LongName": "Large Sinhala ASR training data set", "Category": "Speech", "Summary": "Sinhala ASR training data set containing ~185K utterances", "Files": [ "asr_sinhala_0.zip", "asr_sinhala_1.zip", "asr_sinhala_2.zip", "asr_sinhala_3.zip", "asr_sinhala_4.zip", "asr_sinhala_5.zip", "asr_sinhala_6.zip", "asr_sinhala_7.zip", "asr_sinhala_8.zip", "asr_sinhala_9.zip", "asr_sinhala_a.zip", "asr_sinhala_b.zip", "asr_sinhala_c.zip", "asr_sinhala_d.zip", "asr_sinhala_e.zip", "asr_sinhala_f.zip", ], "IndexFiles": ["asr_sinhala/utt_spk_text.tsv"] * 16, "DataDirs": ["asr_sinhala/data"] * 16, }, "SLR53": { "Language": "Bengali", "LongName": "Large Bengali ASR training data set", "Category": "Speech", "Summary": "Bengali ASR training data set containing ~196K utterances", "Files": [ "asr_bengali_0.zip", "asr_bengali_1.zip", "asr_bengali_2.zip", "asr_bengali_3.zip", "asr_bengali_4.zip", "asr_bengali_5.zip", "asr_bengali_6.zip", "asr_bengali_7.zip", "asr_bengali_8.zip", "asr_bengali_9.zip", "asr_bengali_a.zip", "asr_bengali_b.zip", "asr_bengali_c.zip", "asr_bengali_d.zip", "asr_bengali_e.zip", "asr_bengali_f.zip", ], "IndexFiles": ["asr_bengali/utt_spk_text.tsv"] * 16, "DataDirs": ["asr_bengali/data"] * 16, }, "SLR54": { "Language": "Nepali", "LongName": "Large Nepali ASR training data set", "Category": "Speech", "Summary": "Nepali ASR training data set containing ~157K utterances", "Files": [ "asr_nepali_0.zip", "asr_nepali_1.zip", "asr_nepali_2.zip", "asr_nepali_3.zip", "asr_nepali_4.zip", "asr_nepali_5.zip", "asr_nepali_6.zip", "asr_nepali_7.zip", "asr_nepali_8.zip", "asr_nepali_9.zip", "asr_nepali_a.zip", "asr_nepali_b.zip", "asr_nepali_c.zip", "asr_nepali_d.zip", "asr_nepali_e.zip", "asr_nepali_f.zip", ], "IndexFiles": ["asr_nepali/utt_spk_text.tsv"] * 16, "DataDirs": ["asr_nepali/data"] * 16, }, "SLR63": { "Language": "Malayalam", "LongName": "Crowdsourced high-quality Malayalam multi-speaker speech data set", "Category": "Speech", "Summary": "Data set which contains recordings of native speakers of Malayalam", "Files": ["ml_in_female.zip", "ml_in_male.zip"], "IndexFiles": ["line_index.tsv", "line_index.tsv"], "DataDirs": ["", ""], }, "SLR64": { "Language": "Marathi", "LongName": "Crowdsourced high-quality Marathi multi-speaker speech data set", "Category": "Speech", "Summary": "Data set which contains recordings of native speakers of Marathi", "Files": ["mr_in_female.zip"], "IndexFiles": ["line_index.tsv"], "DataDirs": ["", ""], }, "SLR65": { "Language": "Tamil", "LongName": "Crowdsourced high-quality Tamil multi-speaker speech data set", "Category": "Speech", "Summary": "Data set which contains recordings of native speakers of Tamil", "Files": ["ta_in_female.zip", "ta_in_male.zip"], "IndexFiles": ["line_index.tsv", "line_index.tsv"], "DataDirs": ["", ""], }, "SLR66": { "Language": "Telugu", "LongName": "Crowdsourced high-quality Telugu multi-speaker speech data set", "Category": "Speech", "Summary": "Data set which contains recordings of native speakers of Telugu", "Files": ["te_in_female.zip", "te_in_male.zip"], "IndexFiles": ["line_index.tsv", "line_index.tsv"], "DataDirs": ["", ""], }, "SLR69": { "Language": "Catalan", "LongName": "Crowdsourced high-quality Catalan speech data set", "Category": "Speech", "Summary": "Data set which contains recordings of Catalan", "Files": ["ca_es_female.zip", "ca_es_male.zip"], "IndexFiles": ["line_index.tsv", "line_index.tsv"], "DataDirs": ["", ""], }, "SLR70": { "Language": "Nigerian English", "LongName": "Crowdsourced high-quality Nigerian English speech data set", "Category": "Speech", "Summary": "Data set which contains recordings of Nigerian English", "Files": ["en_ng_female.zip", "en_ng_male.zip"], "IndexFiles": ["line_index.tsv", "line_index.tsv"], "DataDirs": ["", ""], }, "SLR71": { "Language": "Chilean Spanish", "LongName": "Crowdsourced high-quality Chilean Spanish speech data set", "Category": "Speech", "Summary": "Data set which contains recordings of Chilean Spanish", "Files": ["es_cl_female.zip", "es_cl_male.zip"], "IndexFiles": ["line_index.tsv", "line_index.tsv"], "DataDirs": ["", ""], }, "SLR72": { "Language": "Columbian Spanish", "LongName": "Crowdsourced high-quality Columbian Spanish speech data set", "Category": "Speech", "Summary": "Data set which contains recordings of Columbian Spanish", "Files": ["es_co_female.zip", "es_co_male.zip"], "IndexFiles": ["line_index.tsv", "line_index.tsv"], "DataDirs": ["", ""], }, "SLR73": { "Language": "Peruvian Spanish", "LongName": "Crowdsourced high-quality Peruvian Spanish speech data set", "Category": "Speech", "Summary": "Data set which contains recordings of Peruvian Spanish", "Files": ["es_pe_female.zip", "es_pe_male.zip"], "IndexFiles": ["line_index.tsv", "line_index.tsv"], "DataDirs": ["", ""], }, "SLR74": { "Language": "Puerto Rico Spanish", "LongName": "Crowdsourced high-quality Puerto Rico Spanish speech data set", "Category": "Speech", "Summary": "Data set which contains recordings of Puerto Rico Spanish", "Files": ["es_pr_female.zip"], "IndexFiles": ["line_index.tsv"], "DataDirs": [""], }, "SLR75": { "Language": "Venezuelan Spanish", "LongName": "Crowdsourced high-quality Venezuelan Spanish speech data set", "Category": "Speech", "Summary": "Data set which contains recordings of Venezuelan Spanish", "Files": ["es_ve_female.zip", "es_ve_male.zip"], "IndexFiles": ["line_index.tsv", "line_index.tsv"], "DataDirs": ["", ""], }, "SLR76": { "Language": "Basque", "LongName": "Crowdsourced high-quality Basque speech data set", "Category": "Speech", "Summary": "Data set which contains recordings of Basque", "Files": ["eu_es_female.zip", "eu_es_male.zip"], "IndexFiles": ["line_index.tsv", "line_index.tsv"], "DataDirs": ["", ""], }, "SLR77": { "Language": "Galician", "LongName": "Crowdsourced high-quality Galician speech data set", "Category": "Speech", "Summary": "Data set which contains recordings of Galician", "Files": ["gl_es_female.zip", "gl_es_male.zip"], "IndexFiles": ["line_index.tsv", "line_index.tsv"], "DataDirs": ["", ""], }, "SLR78": { "Language": "Gujarati", "LongName": "Crowdsourced high-quality Gujarati multi-speaker speech data set", "Category": "Speech", "Summary": "Data set which contains recordings of native speakers of Gujarati", "Files": ["gu_in_female.zip", "gu_in_male.zip"], "IndexFiles": ["line_index.tsv", "line_index.tsv"], "DataDirs": ["", ""], }, "SLR79": { "Language": "Kannada", "LongName": "Crowdsourced high-quality Kannada multi-speaker speech data set", "Category": "Speech", "Summary": "Data set which contains recordings of native speakers of Kannada", "Files": ["kn_in_female.zip", "kn_in_male.zip"], "IndexFiles": ["line_index.tsv", "line_index.tsv"], "DataDirs": ["", ""], }, "SLR80": { "Language": "Burmese", "LongName": "Crowdsourced high-quality Burmese speech data set", "Category": "Speech", "Summary": "Data set which contains recordings of Burmese", "Files": ["my_mm_female.zip"], "IndexFiles": ["line_index.tsv"], "DataDirs": [""], }, "SLR86": { "Language": "Yoruba", "LongName": "Crowdsourced high-quality Yoruba speech data set", "Category": "Speech", "Summary": "Data set which contains recordings of Yoruba", "Files": ["yo_ng_female.zip", "yo_ng_male.zip"], "IndexFiles": ["line_index.tsv", "line_index.tsv"], "DataDirs": ["", ""], }, } class OpenSlrConfig(datasets.BuilderConfig): """BuilderConfig for OpenSlr.""" def __init__(self, name, **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. """ self.language = kwargs.pop("language", None) self.long_name = kwargs.pop("long_name", None) self.category = kwargs.pop("category", None) self.summary = kwargs.pop("summary", None) self.files = kwargs.pop("files", None) self.index_files = kwargs.pop("index_files", None) self.data_dirs = kwargs.pop("data_dirs", None) description = ( f"Open Speech and Language Resources dataset in {self.language}. Name: {self.name}, " f"Summary: {self.summary}." ) super(OpenSlrConfig, self).__init__(name=name, description=description, **kwargs) class OpenSlr(datasets.GeneratorBasedBuilder): DEFAULT_WRITER_BATCH_SIZE = 32 BUILDER_CONFIGS = [ OpenSlrConfig( name=resource_id, language=_RESOURCES[resource_id]["Language"], long_name=_RESOURCES[resource_id]["LongName"], category=_RESOURCES[resource_id]["Category"], summary=_RESOURCES[resource_id]["Summary"], files=_RESOURCES[resource_id]["Files"], index_files=_RESOURCES[resource_id]["IndexFiles"], data_dirs=_RESOURCES[resource_id]["DataDirs"], ) for resource_id in _RESOURCES.keys() ] def _info(self): features = datasets.Features( { "path": datasets.Value("string"), "audio": datasets.Audio(sampling_rate=48_000), "sentence": datasets.Value("string"), } ) return datasets.DatasetInfo( description=_DESCRIPTION, features=features, supervised_keys=None, homepage=_HOMEPAGE, license=_LICENSE, citation=_CITATION, task_templates=[AutomaticSpeechRecognition(audio_column="audio", transcription_column="sentence")], ) def _split_generators(self, dl_manager): """Returns SplitGenerators.""" resource_number = self.config.name.replace("SLR", "") urls = [f"{_DATA_URL.format(resource_number)}/{file}" for file in self.config.files] if urls[0].endswith(".zip"): dl_paths = dl_manager.download_and_extract(urls) path_to_indexs = [os.path.join(path, f"{self.config.index_files[i]}") for i, path in enumerate(dl_paths)] path_to_datas = [os.path.join(path, f"{self.config.data_dirs[i]}") for i, path in enumerate(dl_paths)] archives = None else: archives = dl_manager.download(urls) path_to_indexs = dl_manager.download(self.config.index_files) path_to_datas = self.config.data_dirs return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={ "path_to_indexs": path_to_indexs, "path_to_datas": path_to_datas, "archive_files": [dl_manager.iter_archive(archive) for archive in archives] if archives else None, }, ), ] def _generate_examples(self, path_to_indexs, path_to_datas, archive_files): """Yields examples.""" counter = -1 if self.config.name in ["SLR35", "SLR36", "SLR52", "SLR53", "SLR54"]: sentence_index = {} for i, path_to_index in enumerate(path_to_indexs): with open(path_to_index, encoding="utf-8") as f: lines = f.readlines() for id_, line in enumerate(lines): field_values = re.split(r"\t\t?", line.strip()) filename, user_id, sentence = field_values sentence_index[filename] = sentence for path_to_data in sorted(Path(path_to_datas[i]).rglob("*.flac")): filename = path_to_data.stem if path_to_data.stem not in sentence_index: continue path = str(path_to_data.resolve()) sentence = sentence_index[filename] counter += 1 yield counter, {"path": path, "audio": path, "sentence": sentence} elif self.config.name in ["SLR32"]: # use archives for path_to_index, path_to_data, files in zip(path_to_indexs, path_to_datas, archive_files): sentences = {} with open(path_to_index, encoding="utf-8") as f: for line in f: # Following regexs are needed to normalise the lines, since the datasets # are not always consistent and have bugs: line = re.sub(r"\t[^\t]*\t", "\t", line.strip()) field_values = re.split(r"\t\t?", line) if len(field_values) != 2: continue filename, sentence = field_values # set absolute path for audio file path = f"{path_to_data}/{filename}.wav" sentences[path] = sentence for path, f in files: if path.startswith(path_to_data): counter += 1 audio = {"path": path, "bytes": f.read()} yield counter, {"path": path, "audio": audio, "sentence": sentences[path]} else: for i, path_to_index in enumerate(path_to_indexs): with open(path_to_index, encoding="utf-8") as f: lines = f.readlines() for id_, line in enumerate(lines): # Following regexs are needed to normalise the lines, since the datasets # are not always consistent and have bugs: line = re.sub(r"\t[^\t]*\t", "\t", line.strip()) field_values = re.split(r"\t\t?", line) if len(field_values) != 2: continue filename, sentence = field_values # set absolute path for audio file path = os.path.join(path_to_datas[i], f"{filename}.wav") counter += 1 yield counter, {"path": path, "audio": path, "sentence": sentence}