# coding=utf-8 | |
# Copyright 2020 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. | |
""" Load norwegian NST dataset provided by National Library of Norway | Språkbanken. | |
Documentation with full description of the data: https://www.nb.no/sbfil/talegjenkjenning/16kHz_2020/no_2020/no-16khz_reorganized_english.pdf | |
TODO: | |
* add multi channel option | |
* add train-validation-test split option | |
* add sample option | |
* add data preview | |
Suggested filtering: | |
* replace("<eeeh>", "") | |
* replace("<mmm>", "") | |
* replace("\\\\Punktum", "") | |
* replace("\\\\Komma", "") | |
""" | |
import json | |
import os | |
from tqdm import tqdm | |
import datasets | |
_DESCRIPTION = """\ | |
This database was created by Nordic Language Technology for the development of automatic speech recognition and dictation in Norwegian. | |
In this version, the organization of the data have been altered to improve the usefulness of the database. | |
In the original version of the material, the files were organized in a specific folder structure where the folder names were meaningful. | |
However, the file names were not meaningful, and there were also cases of files with identical names in different folders. | |
This proved to be impractical, since users had to keep the original folder structure in order to use the data. | |
The files have been renamed, such that the file names are unique and meaningful regardless of the folder structure. | |
The original metadata files were in spl format. These have been converted to JSON format. | |
The converted metadata files are also anonymized and the text encoding has been converted from ANSI to UTF-8. | |
See the documentation file for a full description of the data and the changes made to the database.""" | |
_HOMEPAGE = "https://www.nb.no/sprakbanken/en/resource-catalogue/oai-nb-no-sbr-54/" | |
_LICENSE = "CC0 1.0" | |
# TODO: Add link to the official dataset URLs here | |
# The HuggingFace Datasets library doesn't host the datasets but only points to the original files. | |
# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method) | |
_URLS = { | |
"close_channel": [ | |
"https://www.nb.no/sbfil/talegjenkjenning/16kHz_2020/no_2020/lydfiler_16_1_a.tar.gz", | |
"https://www.nb.no/sbfil/talegjenkjenning/16kHz_2020/no_2020/lydfiler_16_1_b.tar.gz", | |
"https://www.nb.no/sbfil/talegjenkjenning/16kHz_2020/no_2020/lydfiler_16_1_c.tar.gz", | |
"https://www.nb.no/sbfil/talegjenkjenning/16kHz_2020/no_2020/lydfiler_16_1_d.tar.gz", | |
], | |
"distant_channel": [ | |
"https://www.nb.no/sbfil/talegjenkjenning/16kHz_2020/no_2020/lydfiler_16_2_a.tar.gz", | |
"https://www.nb.no/sbfil/talegjenkjenning/16kHz_2020/no_2020/lydfiler_16_2_b.tar.gz", | |
"https://www.nb.no/sbfil/talegjenkjenning/16kHz_2020/no_2020/lydfiler_16_2_c.tar.gz", | |
"https://www.nb.no/sbfil/talegjenkjenning/16kHz_2020/no_2020/lydfiler_16_2_d.tar.gz", | |
] | |
# TODO: add handling of multi channel | |
# "multi_channel": "https://www.nb.no/sbfil/talegjenkjenning/16kHz_2020/se_2020/lydfiler_16_begge.tar.gz", | |
} | |
_ANNOTATIONS_URL = [ | |
"https://www.nb.no/sbfil/talegjenkjenning/16kHz_2020/no_2020/ADB_NOR_0463.tar.gz", | |
"https://www.nb.no/sbfil/talegjenkjenning/16kHz_2020/no_2020/ADB_NOR_0464.tar.gz", | |
"https://www.nb.no/sbfil/talegjenkjenning/16kHz_2020/no_2020/ADB_OD_Nor.NOR.tar.gz" | |
] | |
class NstNO(datasets.GeneratorBasedBuilder): | |
"""Audio dataset for Swedish ASR provided by National Library of Norawy. | |
Originally, recordings have been made on two channels: a close one and a distant one. | |
Channels have been separated and can be loaded independently. | |
TODO: enable and validate multi_channel | |
Two configurations available: | |
- close_channel | |
- distant_channel | |
Main data and metadata available: | |
- audio file (bytes) | |
- manually annotated transcription (str) | |
- age (str) | |
- gender (str) | |
- region of birth (str) | |
- region of youth (str) | |
- recording session info (object) | |
- recording system (object) | |
- "type" of recording (see detailed documentatin) | |
- common_voice-like structured information | |
(info mentioned above with object structure like common voice dataset for ease of merging) | |
""" | |
VERSION = datasets.Version("1.1.0") | |
# This is an example of a dataset with multiple configurations. | |
# If you don't want/need to define several sub-sets in your dataset, | |
# just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes. | |
# If you need to make complex sub-parts in the datasets with configurable options | |
# You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig | |
# BUILDER_CONFIG_CLASS = MyBuilderConfig | |
# You will be able to load one or the other configurations in the following list with | |
# data = datasets.load_dataset('my_dataset', 'first_domain') | |
# data = datasets.load_dataset('my_dataset', 'second_domain') | |
BUILDER_CONFIGS = [ | |
datasets.BuilderConfig(name="close_channel", version=VERSION, description="Close channel recordings"), | |
datasets.BuilderConfig(name="distant_channel", version=VERSION, description="Distant channel recordings"), | |
] | |
DEFAULT_CONFIG_NAME = "close_channel" # It's not mandatory to have a default configuration. Just use one if it make sense. | |
def _info(self): | |
features_dict = { | |
# "region_of_birth": datasets.Value("string"), | |
# "region_of_youth": datasets.Value("string"), | |
# "remarks": datasets.Value("string"), | |
# "pid": datasets.Value("string"), | |
# "directory": datasets.Value("string"), | |
# "imported_sheet_file": datasets.Value("string"), | |
# "mumber_of_recordings": datasets.Value("string"), | |
# "rec_date": datasets.Value("string"), | |
# "rec_time": datasets.Value("string"), | |
# "record_duration": datasets.Value("string"), | |
# "record_session": datasets.Value("string"), | |
# "sheet_number": datasets.Value("string"), | |
# "ansi_codepage": datasets.Value("string"), | |
# "board": datasets.Value("string"), | |
# "byte_format": datasets.Value("string"), | |
# "channels": datasets.Value("string"), | |
# "character_set": datasets.Value("string"), | |
# "coding": datasets.Value("string"), | |
# "dos_codepage": datasets.Value("string"), | |
# "delimiter": datasets.Value("string"), | |
# "frequency": datasets.Value("string"), | |
# "memo": datasets.Value("string"), | |
# "script": datasets.Value("string"), | |
# "version": datasets.Value("string"), | |
# real sampling rate is 16000 | |
# it is set to 48000 to allow concatenation | |
# with common voice dataset using | |
# datasets.concatenate_datasets([dataset_a, dataset_b]) | |
"audio": datasets.features.Audio(sampling_rate=48000), | |
'client_id': datasets.Value("string"), | |
'path': datasets.Value("string"), | |
'sentence': datasets.Value("string"), | |
'up_votes': datasets.Value("int64"), | |
'down_votes': datasets.Value("int64"), | |
'age': datasets.Value("string"), | |
'sex': datasets.Value("string"), | |
'accent': datasets.Value("string"), | |
'locale': datasets.Value("string"), | |
'segment': datasets.Value("string"), | |
'channel': datasets.Value("string") | |
} | |
return datasets.DatasetInfo( | |
# This is the description that will appear on the datasets page. | |
description=_DESCRIPTION, | |
# This defines the different columns of the dataset and their types | |
features=datasets.Features(features_dict), | |
# Here we define them above because they are different between the two configurations | |
# If there's a common (input, target) tuple from the features, uncomment supervised_keys line below and | |
# specify them. They'll be used if as_supervised=True in builder.as_dataset. | |
# supervised_keys=("sentence", "label"), | |
# Homepage of the dataset for documentation | |
homepage=_HOMEPAGE, | |
# License for the dataset if available | |
license=_LICENSE, | |
) | |
def _split_generators(self, dl_manager): | |
# TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration | |
# If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name | |
# dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS | |
# It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files. | |
# By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive | |
urls = _URLS[self.config.name] | |
data_dirs = dl_manager.download_and_extract(urls) | |
annotations_dirs = dl_manager.download_and_extract(_ANNOTATIONS_URL) | |
print(f"data dirs: {data_dirs}") | |
print(f"annotation dirs: {annotations_dirs}") | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.TRAIN, | |
# These kwargs will be passed to _generate_examples | |
gen_kwargs={ | |
"data_dirs": data_dirs, | |
"annotations_dirs": annotations_dirs | |
}, | |
), | |
# TODO: add split handling | |
# datasets.SplitGenerator( | |
# name=datasets.Split.TRAIN, | |
# # These kwargs will be passed to _generate_examples | |
# gen_kwargs={ | |
# "filepath": os.path.join(data_dir, "test.jsonl"), | |
# "split": "test" | |
# }, | |
# ), | |
# datasets.SplitGenerator( | |
# name=datasets.Split.TEST, | |
# # These kwargs will be passed to _generate_examples | |
# gen_kwargs={ | |
# "filepath": os.path.join(data_dir, "test.jsonl"), | |
# "split": "test" | |
# }, | |
# ), | |
# datasets.SplitGenerator( | |
# name=datasets.Split.VALIDATION, | |
# # These kwargs will be passed to _generate_examples | |
# gen_kwargs={ | |
# "filepath": os.path.join(data_dir, "dev.jsonl"), | |
# "split": "dev", | |
# }, | |
# ), | |
] | |
# method parameters are unpacked from `gen_kwargs` as given in `_split_generators` | |
def _generate_examples(self, data_dirs, annotations_dirs): | |
if self.config.name == "close_channel": | |
channel_ext = "-1" | |
else: | |
channel_ext = "-2" | |
for annotations_dir in annotations_dirs: | |
annotations_files = os.listdir(annotations_dir) | |
for annotation_filename in tqdm(annotations_files): | |
annotations_filepath = os.path.join(annotations_dir, annotation_filename) | |
with open(annotations_filepath, "r") as f: | |
annotation = json.load(f) | |
if "val_recordings" in annotation: | |
val_recordings = annotation["val_recordings"] | |
for recording in val_recordings: | |
# channel_ext in can either be "-1" "-2" | |
# so if file is "123456.wav" | |
# close channel file is "123456-1.wav" | |
# distant channel file is "123456-2.wav" | |
rel_filepath = f'no/{annotation["pid"]}/{annotation["pid"]}_{recording["file"]}'.replace(".wav", f"{channel_ext}.wav") | |
for data_dir in data_dirs: | |
audio_filepath = f"{data_dir}/{rel_filepath}" | |
if os.path.exists(audio_filepath): | |
with open(audio_filepath, "rb") as f: | |
audio_bytes = f.read() | |
result = { | |
# "region_of_birth": annotation["info"]["Region_of_Birth"] or "", | |
# "region_of_youth": annotation["info"]["Region_of_Youth"] or "", | |
# "remarks": annotation["info"]["Remarks"] or "", | |
# "pid": annotation["pid"] or "", | |
# "directory": annotation["session"]["Directory"] or "", | |
# "imported_sheet_file": annotation["session"]["Imported_sheet_file"] or "", | |
# "mumber_of_recordings": annotation["session"]["Number_of_recordings"] or "", | |
# "rec_date": annotation["session"]["RecDate"] or "", | |
# "rec_time": annotation["session"]["RecTime"] or "", | |
# "record_duration": annotation["session"]["Record_duration"] or "", | |
# "record_session": annotation["session"]["Record_session"] or "", | |
# "sheet_number": annotation["session"]["Sheet_number"] or "", | |
# "ansi_codepage": annotation["system"]["ANSI_Codepage"] or "", | |
# "board": annotation["system"]["Board"] or "", | |
# "byte_format": annotation["system"]["ByteFormat"] or "", | |
# "channels": annotation["system"]["Channels"] or "", | |
# "character_set": annotation["system"]["CharacterSet"] or "", | |
# "coding": annotation["system"]["Coding"] or "", | |
# "dos_codepage": annotation["system"]["DOS_Codepage"] or "", | |
# "delimiter": annotation["system"]["Delimiter"] or "", | |
# "frequency": annotation["system"]["Frequency"] or "", | |
# "memo": annotation["system"]["Memo"] or "", | |
# "script": annotation["system"]["Script"] or "", | |
# "version": annotation["system"]["Version"] or "", | |
"audio": {"path": rel_filepath, "bytes": audio_bytes}, | |
'client_id': annotation["info"]["Speaker_ID"] or "", | |
'path': rel_filepath, | |
'sentence': recording["text"], | |
'up_votes': 1, | |
'down_votes': 0, | |
'age': annotation["info"]["Age"] or "", | |
'sex': annotation["info"]["Sex"] or "", | |
'accent': "", | |
'locale': "sv", | |
'segment': "", | |
'channel': self.config.name or "" | |
} | |
yield rel_filepath, result | |