Update openslr-nepali-asr-cleaned.py

openslr-nepali-asr-cleaned.py

@@ -1,24 +1,7 @@
-# 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.
-"""Leading and Trailing Silences Removed Large Nepali ASR Dataset"""
-
 import os
 import csv
-
 import datasets
 
-
 _CITATION = """\
 @inproceedings{kjartansson-etal-sltu2018,
 title = {{Crowd-Sourced Speech Corpora for Javanese, Sundanese,  Sinhala, Nepali, and Bangladeshi Bengali}},
@@ -35,19 +18,12 @@ URL   = {http://dx.doi.org/10.21437/SLTU.2018-11}
 _DESCRIPTION = """\
 This data set contains transcribed audio data for Nepali. The data set consists of flac files, and a TSV file. The file utt_spk_text.tsv contains a FileID, anonymized UserID and the transcription of audio in the file.
 The data set has been manually quality checked, but there might still be errors.
-
 The audio files are sampled at rate of 16KHz, and leading and trailing silences are trimmed using torchaudio's voice activity detection.
 """
 
-# Official homepage for the dataset
 _HOMEPAGE = "https://www.openslr.org/54/"
-
-# The licence for the dataset
 _LICENSE = "license:cc-by-sa-4.0"
 
-# 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 = {
     'cleaned': {
         "index_file": "https://huggingface.co/datasets/spktsagar/openslr-nepali-asr-cleaned/resolve/main/data/utt_spk_text_clean.tsv",
@@ -66,20 +42,14 @@ _URLS = {
 }
 
 
-# TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case
 class OpenslrNepaliAsrCleaned(datasets.GeneratorBasedBuilder):
-    """End Silences Removed Large Nepali ASR Dataset"""
-
     VERSION = datasets.Version("1.0.0")
 
     BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name="original", version=VERSION,
-                               description="All original utterances, speaker id and transcription from Openslr Large Nepali ASR Dataset"),
-        datasets.BuilderConfig(name="cleaned", version=VERSION,
-                               description="All cleaned utterances, speaker id and transcription from Openslr Large Nepali ASR Dataset"),
+        datasets.BuilderConfig(name="original", version=VERSION, description="All original utterances, speaker id and transcription from Openslr Large Nepali ASR Dataset"),
+        datasets.BuilderConfig(name="cleaned", version=VERSION, description="All cleaned utterances, speaker id and transcription from Openslr Large Nepali ASR Dataset"),
     ]
 
-    # It's not mandatory to have a default configuration. Just use one if it make sense.
     DEFAULT_CONFIG_NAME = "original"
 
     def _info(self):
@@ -94,16 +64,9 @@ class OpenslrNepaliAsrCleaned(datasets.GeneratorBasedBuilder):
         )
         return datasets.DatasetInfo(
             description=_DESCRIPTION,
-            # Here we define them above because they are different between the two configurations
             features=features,
-            # 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,
-            # Citation for the dataset
             citation=_CITATION,
             task_templates=[datasets.tasks.AutomaticSpeechRecognition(
                 audio_column="utterance", transcription_column="transcription"