Update parquet files

ASCEND.py

@@ -1,139 +0,0 @@
-# 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.
-""" Common Voice Dataset"""
-
-from datasets import AutomaticSpeechRecognition
-
-
-import datasets
-import os
-import pandas as pd
-
-
-_CITATION = """\
-@inproceedings{lovenia2021ascend,
-  title     = {ASCEND: A Spontaneous Chinese-English Dataset for Code-switching in Multi-turn Conversation},
-  author    = {Lovenia, Holy and Cahyawijaya, Samuel and Winata, Genta Indra and Xu, Peng and Yan, Xu and Liu, Zihan and Frieske, Rita and Yu, Tiezheng and Dai, Wenliang and Barezi, Elham J and others},
-  booktitle = {Proceedings of the International Conference on Language Resources and Evaluation, {LREC} 2022, 20-25 June 2022, Lu Palais du Pharo, France},
-  publisher = {European Language Resources Association},
-  year      = {2022},
-  pages = {}
-}
-"""
-
-_DESCRIPTION = """\
-ASCEND (A Spontaneous Chinese-English Dataset) introduces a high-quality resource of spontaneous multi-turn conversational dialogue Chinese-English code-switching corpus collected in Hong Kong. ASCEND consists of 10.62 hours of spontaneous speech with a total of ~12.3K utterances. The corpus is split into 3 sets: training, validation, and test with a ratio of 8:1:1 while maintaining a balanced gender proportion on each set.
-"""
-
-_HOMEPAGE = "https://huggingface.co/datasets/CAiRE/ASCEND"
-
-_URL = "https://huggingface.co/datasets/CAiRE/ASCEND/raw/main/"
-_URLS = {
-    "train": _URL + "train_metadata.csv",
-    "test": _URL + "test_metadata.csv",
-    "validation": _URL + "validation_metadata.csv",
-    "waves": "https://huggingface.co/datasets/CAiRE/ASCEND/resolve/main/waves.tar.bz2",
-}
-
-
-class ASCENDConfig(datasets.BuilderConfig):
-    """BuilderConfig for ASCEND."""
-
-    def __init__(self, name="main", **kwargs):
-        """
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(ASCENDConfig, self).__init__(name, **kwargs)
-
-
-class ASCEND(datasets.GeneratorBasedBuilder):
-    """ASCEND: A Spontaneous Chinese-English Dataset for code-switching. Snapshot date: 5 January 2022."""
-
-    BUILDER_CONFIGS = [
-        ASCENDConfig(
-            name="main",
-            version=datasets.Version("1.0.0", ""),
-            description=_DESCRIPTION,
-        )
-    ]
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                "id": datasets.Value("string"),
-                "path": datasets.Value("string"),
-                "audio": datasets.Audio(sampling_rate=16_000),
-                "transcription": datasets.Value("string"),
-                "duration": datasets.Value("float32"),
-                "language": datasets.Value("string"),
-                "original_speaker_id": datasets.Value("int64"),
-                "session_id": datasets.Value("int64"),
-                "topic": datasets.Value("string"),
-            }
-        )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            citation=_CITATION,
-            task_templates=[AutomaticSpeechRecognition(audio_column="audio", transcription_column="transcription")],
-        )
-
-    def _split_generators(self, dl_manager):
-        downloaded_files = dl_manager.download_and_extract(_URLS)
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "metadata_path": downloaded_files["train"],
-                    "wave_path": downloaded_files["waves"],
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={
-                    "metadata_path": downloaded_files["test"],
-                    "wave_path": downloaded_files["waves"],
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={
-                    "metadata_path": downloaded_files["validation"],
-                    "wave_path": downloaded_files["waves"],
-                },
-            ),
-        ]
-
-    def _generate_examples(self, metadata_path, wave_path):
-        print(metadata_path)
-        metadata_df = pd.read_csv(metadata_path)
-
-        for index, row in metadata_df.iterrows():
-            example = {
-                "id": str(index).zfill(5),
-                "path": os.path.join(wave_path, row["file_name"]),
-                "audio": os.path.join(wave_path, row["file_name"]),
-                "transcription": row["transcription"],
-                "duration": row["duration"],
-                "language": row["language"],
-                "original_speaker_id": row["original_speaker_id"],
-                "session_id": row["session_id"],
-                "topic": row["topic"],
-            }
-            yield index, example

README.md

@@ -1,116 +0,0 @@
----
-annotations_creators:
-- expert-generated
-language_creators:
-- crowdsourced
-language:
-- en
-- zh
-license:
-- cc-by-sa-4.0
-multilinguality:
-- multilingual
-size_categories:
-- 10K<n<100K
-source_datasets:
-- original
-task_categories:
-- automatic-speech-recognition
-task_ids: []
-pretty_name: 'ASCEND: A Spontaneous Chinese-English Dataset for Code-switching in
-  Multi-turn Conversation'
-tags:
-- speech-recognition
-- code-switching
----
-
-# Dataset Card for ASCEND
-
-## Table of Contents
-- [Dataset Description](#dataset-description)
-  - [Dataset Summary](#dataset-summary)
-  - [Supported Tasks](#supported-tasks-and-leaderboards)
-  - [Languages](#languages)
-- [Usage](#usage)
-- [Dataset Structure](#dataset-structure)
-  - [Data Splits](#data-instances)
-- [Additional Information](#additional-information)
-  - [Licensing Information](#licensing-information)
-  - [Citation Information](#citation-information)
-
-## Dataset Description
-
-- **Homepage:** [Needs More Information]
-- **Repository:** [Needs More Information]
-- **Paper:** https://arxiv.org/abs/2112.06223
-- **Leaderboard:** [Needs More Information]
-- **Point of Contact:** [Needs More Information]
-
-### Dataset Summary
-
-ASCEND (A Spontaneous Chinese-English Dataset) introduces a high-quality resource of spontaneous multi-turn conversational dialogue Chinese-English code-switching corpus collected in Hong Kong. ASCEND consists of 10.62 hours of spontaneous speech with a total of ~12.3K utterances. The corpus is split into 3 sets: training, validation, and test with a ratio of 8:1:1 while maintaining a balanced gender proportion on each set.
-
-### Supported Tasks and Leaderboards
-
-Code-switching
-
-### Languages
-
-Chinese and English
-
-## Usage
-
-To obtain the full dataset (complete with train, validation, and test set), simply run this:
-
-```
-import datasets
-dataset = datasets.load_dataset("CAiRE/ASCEND")
-```
-
-## Dataset Structure
-
-A typical data point comprises the path to the audio file, the loaded audio array, and its transcription. Additional fields include datapoint id, duration, language, speaker id, session id, and topic.
-
-```
-{
-	'id': '00644',
-	'path': '.cache/huggingface/datasets/downloads/extracted/f0b33b5266cd9452ee310eef3577cf7adb7f29aa54dbff74b9a8ee406a55d614/waves/ses2_spk3_L13101_189.900_5.490.wav',
-	'audio': {
-		'path': '.cache/huggingface/datasets/downloads/extracted/f0b33b5266cd9452ee310eef3577cf7adb7f29aa54dbff74b9a8ee406a55d614/waves/ses2_spk3_L13101_189.900_5.490.wav',
-		'array': array([-6.1035156e-05, -1.8310547e-04, 3.0517578e-05, ...,
-			0.0000000e+00, -3.0517578e-05, 0.0000000e+00
-		], dtype = float32),
-		'sampling_rate': 16000
-	},
-	'transcription': '因为你不可能邀你的female friends去说走我们去play basketball',
-	'duration': 5.489999771118164,
-	'language': 'mixed',
-	'original_speaker_id': 3,
-	'session_id': 2,
-	'topic': 'sports'
-}
-```
-
-### Data Splits
-
-Number of utterances: 9,869 train, 1,130 validation, and 1,315 test.
-
-## Additional Information
-
-For comprehensive explanations, please check [our paper](https://arxiv.org/pdf/2112.06223.pdf).
-
-### Licensing Information
-
-Creative Common Attribution Share-Alike 4.0 International (CC-BY-SA 4.0)
-
-### Citation Information
-
-If you use our dataset, please cite us:
-
-```
-@inproceedings{lovenia2022ascend,
-  title={ASCEND: A Spontaneous Chinese-English Dataset for Code-switching in Multi-turn Conversation},
-  author={Lovenia, Holy and Cahyawijaya, Samuel and Winata, Genta Indra and Xu, Peng and Yan, Xu and Liu, Zihan and Frieske, Rita and Yu, Tiezheng and Dai, Wenliang and Barezi, Elham J and others},
-  booktitle={Proceedings of the 13th Language Resources and Evaluation Conference (LREC)},
-  year={2022}
- ```

dataset_infos.json

@@ -1 +0,0 @@
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speakers.csv

@@ -1,24 +0,0 @@
-speaker_id,age,gender,split,years_in_english_study,english_score
-1,23,female,train,17,6
-2,22,male,train,13,6
-3,25,male,test,15,6
-4,24,male,train,10,7.5
-5,24,female,train,12,7
-6,30,female,train,12,7
-7,23,female,val,17,7
-8,23,female,train,15,6
-9,27,male,train,12,6
-10,23,male,train,12,6
-11,23,female,train,16,8
-12,23,male,val,10,5.5
-13,23,female,train,16,7
-14,22,female,train,12,6.5
-15,19,female,train,8,7
-16,26,male,train,15,6.5
-17,24,female,test,11,6.5
-18,23,male,train,5,6.5
-19,26,male,train,16,7
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-21,23,female,train,15,6.5
-24,27,male,train,17,6
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