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Update files from the datasets library (from 1.16.0)

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Release notes: https://github.com/huggingface/datasets/releases/tag/1.16.0

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README.md ADDED
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+ ---
2
+ annotations_creators:
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+ - machine-generated
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+ language_creators:
5
+ - crowdsourced
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+ languages:
7
+ - en
8
+ - hi
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+ licenses:
10
+ - cc-by-sa-3-0
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+ - gfdl-1-3-or-later
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+ multilinguality:
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+ - multilingual
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+ - translation
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+ pretty_name: CMU Document Grounded Conversations
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+ size_categories:
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+ - 1K<n<10K
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+ source_datasets:
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+ - original
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+ task_categories:
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+ - conditional-text-generation
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+ task_ids:
23
+ - machine-translation
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+ ---
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+
26
+ # Dataset Card for CMU Document Grounded Conversations
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+
28
+ ## Table of Contents
29
+ - [Dataset Description](#dataset-description)
30
+ - [Dataset Summary](#dataset-summary)
31
+ - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
32
+ - [Languages](#languages)
33
+ - [Dataset Structure](#dataset-structure)
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+ - [Data Instances](#data-instances)
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+ - [Data Fields](#data-fields)
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+ - [Data Splits](#data-splits)
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+ - [Dataset Creation](#dataset-creation)
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+ - [Curation Rationale](#curation-rationale)
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+ - [Source Data](#source-data)
40
+ - [Annotations](#annotations)
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+ - [Personal and Sensitive Information](#personal-and-sensitive-information)
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+ - [Considerations for Using the Data](#considerations-for-using-the-data)
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+ - [Social Impact of Dataset](#social-impact-of-dataset)
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+ - [Discussion of Biases](#discussion-of-biases)
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+ - [Other Known Limitations](#other-known-limitations)
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+ - [Additional Information](#additional-information)
47
+ - [Dataset Curators](#dataset-curators)
48
+ - [Licensing Information](#licensing-information)
49
+ - [Citation Information](#citation-information)
50
+ - [Contributions](#contributions)
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+
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+ ## Dataset Description
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+
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+ - **Homepage:** [CMU Hinglish DoG](http://festvox.org/cedar/data/notyet/)
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+ - **Repository:** [CMU Document Grounded Conversations (English version)](https://github.com/festvox/datasets-CMU_DoG)
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+ - **Paper:** [CMU Document Grounded Conversations (English version)](https://arxiv.org/pdf/1809.07358.pdf)
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+ - **Point of Contact:**
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+
59
+ ### Dataset Summary
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+
61
+ This is a collection of text conversations in Hinglish (code mixing between Hindi-English) and their corresponding English versions. Can be used for Translating between the two. The dataset has been provided by Prof. Alan Black's group from CMU.
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+
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+ ### Supported Tasks and Leaderboards
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+
65
+ - `abstractive-mt`
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+
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+ ### Languages
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+
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+ ## Dataset Structure
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+
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+ ### Data Instances
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+
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+ A typical data point comprises a Hinglish text, with key `hi_en` and its English version with key `en`. The `docIdx` contains the current section index of the wiki document when the utterance is said. There are in total 4 sections for each document. The `uid` has the user id of this utterance.
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+
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+ An example from the CMU_Hinglish_DoG train set looks as follows:
76
+ ```
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+ {'rating': 2,
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+ 'wikiDocumentIdx': 13,
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+ 'utcTimestamp': '2018-03-16T17:48:22.037Z',
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+ 'uid': 'user2',
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+ 'date': '2018-03-16T17:47:21.964Z',
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+ 'uid2response': {'response': [1, 2, 3, 5], 'type': 'finish'},
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+ 'uid1LogInTime': '2018-03-16T17:47:21.964Z',
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+ 'user2_id': 'USR664',
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+ 'uid1LogOutTime': '2018-03-16T18:02:29.072Z',
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+ 'whoSawDoc': ['user1', 'user2'],
87
+ 'status': 1,
88
+ 'docIdx': 0,
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+ 'uid1response': {'response': [1, 2, 3, 4], 'type': 'finish'},
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+ 'translation': {'en': 'The director is Zack Snyder, 27% Rotten Tomatoes, 4.9/10.',
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+ 'hi_en': 'Zack Snyder director hai, 27% Rotten Tomatoes, 4.9/10.'}}
92
+ ```
93
+
94
+ ### Data Fields
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+
96
+ - `date`: the time the file is created, as a string
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+ - `docIdx`: the current section index of the wiki document when the utterance is said. There are in total 4 sections for each document.
98
+ - `translation`:
99
+ - `hi_en`: The text in Hinglish
100
+ - `en`: The text in English
101
+ - `uid`: the user id of this utterance.
102
+ - `utcTimestamp`: the server utc timestamp of this utterance, as a string
103
+ - `rating`: A number from 1 or 2 or 3. A larger number means the quality of the conversation is better.
104
+ - `status`: status as an integer
105
+ - `uid1LogInTime`: optional login time of user 1, as a string
106
+ - `uid1LogOutTime`: optional logout time of user 1, as a string
107
+ - `uid1response`: a json object contains the status and response of user after finishing the conversation. Fields in the object includes:
108
+ - `type`: should be one of ['finish', 'abandon','abandonWithouAnsweringFeedbackQuestion']. 'finish' means the user successfully finishes the conversation, either by completing 12 or 15 turns or in the way that the other user leaves the conversation first. 'abandon' means the user abandons the conversation in the middle, but entering the feedback page. 'abandonWithouAnsweringFeedbackQuestion' means the user just disconnects or closes the web page without providing the feedback.
109
+ - `response`: the answer to the post-conversation questions. The worker can choose multiple of them. The options presented to the user are as follows:
110
+ For type 'finish'
111
+ 1: The conversation is understandable.
112
+ 2: The other user is actively responding me.
113
+ 3: The conversation goes smoothly.
114
+ For type 'abandon'
115
+ 1: The other user is too rude.
116
+ 2: I don't know how to proceed with the conversation.
117
+ 3: The other user is not responding to me.
118
+ For users given the document
119
+ 4: I have watched the movie before.
120
+ 5: I have not watched the movie before.
121
+ For the users without the document
122
+ 4: I will watch the movie after the other user's introduction.
123
+ 5: I will not watch the movie after the other user's introduction.
124
+ - `uid2response`: same as uid1response
125
+ - `user2_id`: the generated user id of user 2
126
+ - `whoSawDoc`: Should be one of ['user1'], ['user2'], ['user1', 'user2']. Indicating which user read the document.
127
+ - `wikiDocumentId`: the index of the wiki document.
128
+
129
+ ### Data Splits
130
+
131
+ | name |train|validation|test|
132
+ |----------|----:|---------:|---:|
133
+ |CMU DOG | 8060| 942| 960|
134
+
135
+ ## Dataset Creation
136
+
137
+ [More Information Needed]
138
+
139
+ ### Curation Rationale
140
+
141
+ [More Information Needed]
142
+
143
+ ### Source Data
144
+
145
+ The Hinglish dataset is derived from the original CMU DoG (Document Grounded Conversations Dataset). More info about that can be found in the [repo](https://github.com/festvox/datasets-CMU_DoG)
146
+
147
+ #### Initial Data Collection and Normalization
148
+
149
+ [More Information Needed]
150
+
151
+ #### Who are the source language producers?
152
+
153
+ [More Information Needed]
154
+
155
+ ### Annotations
156
+
157
+ [More Information Needed]
158
+
159
+ #### Annotation process
160
+
161
+ [More Information Needed]
162
+
163
+ #### Who are the annotators?
164
+
165
+ [More Information Needed]
166
+
167
+ ### Personal and Sensitive Information
168
+
169
+ [More Information Needed]
170
+
171
+ ## Considerations for Using the Data
172
+
173
+ ### Social Impact of Dataset
174
+
175
+ The purpose of this dataset is to help develop better question answering systems.
176
+
177
+
178
+ ### Discussion of Biases
179
+
180
+ [More Information Needed]
181
+
182
+ ### Other Known Limitations
183
+
184
+ [More Information Needed]
185
+
186
+ ## Additional Information
187
+
188
+ ### Dataset Curators
189
+
190
+ The dataset was initially created by Prof Alan W Black's group at CMU
191
+
192
+ ### Licensing Information
193
+
194
+ [More Information Needed]
195
+
196
+ ### Citation Information
197
+
198
+ ```bibtex
199
+ @inproceedings{
200
+ cmu_dog_emnlp18,
201
+ title={A Dataset for Document Grounded Conversations},
202
+ author={Zhou, Kangyan and Prabhumoye, Shrimai and Black, Alan W},
203
+ year={2018},
204
+ booktitle={Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing}
205
+ }
206
+ ```
207
+
208
+ ### Contributions
209
+
210
+ Thanks to [@Ishan-Kumar2](https://github.com/Ishan-Kumar2) for adding this dataset.
cmu_hinglish_dog.py ADDED
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1
+ # coding=utf-8
2
+ # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
3
+ #
4
+ # Licensed under the Apache License, Version 2.0 (the "License");
5
+ # you may not use this file except in compliance with the License.
6
+ # You may obtain a copy of the License at
7
+ #
8
+ # http://www.apache.org/licenses/LICENSE-2.0
9
+ #
10
+ # Unless required by applicable law or agreed to in writing, software
11
+ # distributed under the License is distributed on an "AS IS" BASIS,
12
+ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13
+ # See the License for the specific language governing permissions and
14
+ # limitations under the License.
15
+
16
+ import json
17
+ import os
18
+ import re
19
+
20
+ import datasets
21
+
22
+
23
+ _CITATION = """\
24
+ @inproceedings{cmu_dog_emnlp18,
25
+ title={A Dataset for Document Grounded Conversations},
26
+ author={Zhou, Kangyan and Prabhumoye, Shrimai and Black, Alan W},
27
+ year={2018},
28
+ booktitle={Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing}
29
+ }
30
+
31
+ @inproceedings{khanuja-etal-2020-gluecos,
32
+ title = "{GLUEC}o{S}: An Evaluation Benchmark for Code-Switched {NLP}",
33
+ author = "Khanuja, Simran and
34
+ Dandapat, Sandipan and
35
+ Srinivasan, Anirudh and
36
+ Sitaram, Sunayana and
37
+ Choudhury, Monojit",
38
+ booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
39
+ month = jul,
40
+ year = "2020",
41
+ address = "Online",
42
+ publisher = "Association for Computational Linguistics",
43
+ url = "https://www.aclweb.org/anthology/2020.acl-main.329",
44
+ pages = "3575--3585"
45
+ }
46
+ """
47
+
48
+ _DESCRIPTION = """\
49
+ This is a collection of text conversations in Hinglish (code mixing between Hindi-English) and their corresponding English only versions. Can be used for Translating between the two.
50
+ """
51
+
52
+ _HOMEPAGE = "http://festvox.org/cedar/data/notyet/"
53
+ _URL_HINGLISH = "http://festvox.org/cedar/data/notyet/CMUHinglishDoG.zip"
54
+ _URL_ENGLISH = "https://github.com/festvox/datasets-CMU_DoG/archive/master/Conversations.zip"
55
+
56
+
57
+ class CMUHinglishDoG(datasets.GeneratorBasedBuilder):
58
+ """Load the CMU Hinglish DoG Data for MT"""
59
+
60
+ def _info(self):
61
+ features = datasets.Features(
62
+ {
63
+ "date": datasets.Value("string"),
64
+ "docIdx": datasets.Value("int64"),
65
+ "translation": datasets.Translation(languages=["en", "hi_en"]),
66
+ "uid": datasets.Value("string"),
67
+ "utcTimestamp": datasets.Value("string"),
68
+ "rating": datasets.Value("int64"),
69
+ "status": datasets.Value("int64"),
70
+ "uid1LogInTime": datasets.Value("string"),
71
+ "uid1LogOutTime": datasets.Value("string"),
72
+ "uid1response": {
73
+ "response": datasets.Sequence(datasets.Value("int64")),
74
+ "type": datasets.Value("string"),
75
+ },
76
+ "uid2response": {
77
+ "response": datasets.Sequence(datasets.Value("int64")),
78
+ "type": datasets.Value("string"),
79
+ },
80
+ "user2_id": datasets.Value("string"),
81
+ "whoSawDoc": datasets.Sequence(datasets.Value("string")),
82
+ "wikiDocumentIdx": datasets.Value("int64"),
83
+ }
84
+ )
85
+ return datasets.DatasetInfo(
86
+ description=_DESCRIPTION,
87
+ features=features,
88
+ supervised_keys=None,
89
+ homepage=_HOMEPAGE,
90
+ citation=_CITATION,
91
+ )
92
+
93
+ def _split_generators(self, dl_manager):
94
+ """The linking part between Hinglish data and English data is inspired from the implementation in GLUECoS.
95
+ Refer here for the original script https://github.com/microsoft/GLUECoS/blob/7fdc51653e37a32aee17505c47b7d1da364fa77e/Data/Preprocess_Scripts/preprocess_mt_en_hi.py"""
96
+
97
+ eng_path = dl_manager.download_and_extract(_URL_ENGLISH)
98
+ data_dir_en = os.path.join(eng_path, "datasets-CMU_DoG-master", "Conversations")
99
+
100
+ hi_en_path = dl_manager.download_and_extract(_URL_HINGLISH)
101
+ data_dir_hi_en = os.path.join(hi_en_path, "CMUHinglishDoG", "Conversations_Hinglish")
102
+
103
+ hi_en_dirs = {
104
+ "train": os.path.join(data_dir_hi_en, "train"),
105
+ "valid": os.path.join(data_dir_hi_en, "valid"),
106
+ "test": os.path.join(data_dir_hi_en, "test"),
107
+ }
108
+
109
+ return [
110
+ datasets.SplitGenerator(
111
+ name=datasets.Split.TRAIN,
112
+ gen_kwargs={
113
+ "hi_en_dir": hi_en_dirs["train"],
114
+ "data_dir_en": data_dir_en,
115
+ },
116
+ ),
117
+ datasets.SplitGenerator(
118
+ name=datasets.Split.TEST,
119
+ gen_kwargs={
120
+ "hi_en_dir": hi_en_dirs["test"],
121
+ "data_dir_en": data_dir_en,
122
+ },
123
+ ),
124
+ datasets.SplitGenerator(
125
+ name=datasets.Split.VALIDATION,
126
+ gen_kwargs={
127
+ "hi_en_dir": hi_en_dirs["valid"],
128
+ "data_dir_en": data_dir_en,
129
+ },
130
+ ),
131
+ ]
132
+
133
+ def _generate_examples(self, hi_en_dir, data_dir_en):
134
+ """Yields examples."""
135
+ english_files_train = os.listdir(os.path.join(data_dir_en, "train"))
136
+ english_files_val = os.listdir(os.path.join(data_dir_en, "valid"))
137
+ english_files_test = os.listdir(os.path.join(data_dir_en, "test"))
138
+
139
+ hinglish_files = os.listdir(hi_en_dir)
140
+ key = 0
141
+ for f in hinglish_files:
142
+ en_file_path = f.split(".json")[0] + ".json"
143
+ found = True
144
+ # Looks for the corresponding english file in all 3 splits
145
+ if en_file_path in english_files_train:
146
+ en = json.load(open(os.path.join(os.path.join(data_dir_en, "train"), en_file_path)))
147
+ elif en_file_path in english_files_val:
148
+ en = json.load(open(os.path.join(os.path.join(data_dir_en, "valid"), en_file_path)))
149
+ elif en_file_path in english_files_test:
150
+ en = json.load(open(os.path.join(os.path.join(data_dir_en, "test"), en_file_path)))
151
+ else:
152
+ found = False
153
+ if found:
154
+ hi_en = json.load(open(os.path.join(hi_en_dir, f)))
155
+
156
+ assert len(en["history"]) == len(hi_en["history"])
157
+
158
+ for x, y in zip(en["history"], hi_en["history"]):
159
+ assert x["docIdx"] == y["docIdx"]
160
+ assert x["uid"] == y["uid"]
161
+ assert x["utcTimestamp"] == y["utcTimestamp"]
162
+
163
+ x["text"] = re.sub("\t|\n", " ", x["text"])
164
+ y["text"] = re.sub("\t|\n", " ", y["text"])
165
+ line = {
166
+ "date": hi_en["date"],
167
+ "uid": x["uid"],
168
+ "docIdx": x["docIdx"],
169
+ "utcTimestamp": x["utcTimestamp"],
170
+ "translation": {"hi_en": y["text"], "en": x["text"]},
171
+ "rating": hi_en["rating"],
172
+ "status": hi_en["status"],
173
+ "uid1LogOutTime": hi_en.get("uid1LogOutTime"),
174
+ "uid1LogInTime": hi_en["uid1LogInTime"],
175
+ "uid1response": {
176
+ "response": hi_en["uid1response"]["response"] if "uid1response" in hi_en else [],
177
+ "type": hi_en["uid1response"]["type"] if "uid1response" in hi_en else None,
178
+ },
179
+ "uid2response": {
180
+ "response": hi_en["uid2response"]["response"] if "uid2response" in hi_en else [],
181
+ "type": hi_en["uid2response"]["type"] if "uid2response" in hi_en else None,
182
+ },
183
+ "user2_id": hi_en["user2_id"],
184
+ "whoSawDoc": hi_en["whoSawDoc"],
185
+ "wikiDocumentIdx": hi_en["wikiDocumentIdx"],
186
+ }
187
+
188
+ yield key, line
189
+ key += 1
dataset_infos.json ADDED
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1
+ {"default": {"description": "This is a collection of text conversations in Hinglish (code mixing between Hindi-English) and their corresponding English only versions. Can be used for Translating between the two.\n", "citation": "@inproceedings{cmu_dog_emnlp18,\n title={A Dataset for Document Grounded Conversations},\n author={Zhou, Kangyan and Prabhumoye, Shrimai and Black, Alan W},\n year={2018},\n booktitle={Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing}\n}\n\n@inproceedings{khanuja-etal-2020-gluecos,\n title = \"{GLUEC}o{S}: An Evaluation Benchmark for Code-Switched {NLP}\",\n author = \"Khanuja, Simran and\n Dandapat, Sandipan and\n Srinivasan, Anirudh and\n Sitaram, Sunayana and\n Choudhury, Monojit\",\n booktitle = \"Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics\",\n month = jul,\n year = \"2020\",\n address = \"Online\",\n publisher = \"Association for Computational Linguistics\",\n url = \"https://www.aclweb.org/anthology/2020.acl-main.329\",\n pages = \"3575--3585\"\n}\n", "homepage": "http://festvox.org/cedar/data/notyet/", "license": "", "features": {"date": {"dtype": "string", "id": null, "_type": "Value"}, "docIdx": {"dtype": "int64", "id": null, "_type": "Value"}, "translation": {"languages": ["en", "hi_en"], "id": null, "_type": "Translation"}, "uid": {"dtype": "string", "id": null, "_type": "Value"}, "utcTimestamp": {"dtype": "string", "id": null, "_type": "Value"}, "rating": {"dtype": "int64", "id": null, "_type": "Value"}, "status": {"dtype": "int64", "id": null, "_type": "Value"}, "uid1LogInTime": {"dtype": "string", "id": null, "_type": "Value"}, "uid1LogOutTime": {"dtype": "string", "id": null, "_type": "Value"}, "uid1response": {"response": {"feature": {"dtype": "int64", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "type": {"dtype": "string", "id": null, "_type": "Value"}}, "uid2response": {"response": {"feature": {"dtype": "int64", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "type": {"dtype": "string", "id": null, "_type": "Value"}}, "user2_id": {"dtype": "string", "id": null, "_type": "Value"}, "whoSawDoc": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "wikiDocumentIdx": {"dtype": "int64", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "cmu_hinglish_do_g", "config_name": "default", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 3142398, "num_examples": 8060, "dataset_name": "cmu_hinglish_do_g"}, "test": {"name": "test", "num_bytes": 379521, "num_examples": 960, "dataset_name": "cmu_hinglish_do_g"}, "validation": {"name": "validation", "num_bytes": 368726, "num_examples": 942, "dataset_name": "cmu_hinglish_do_g"}}, "download_checksums": {"https://github.com/festvox/datasets-CMU_DoG/archive/master/Conversations.zip": {"num_bytes": 8162724, "checksum": "87e390c091f2114a09160aaa96ca45136d12b3ffd8ec82f1513a81251af0ac32"}, "http://festvox.org/cedar/data/notyet/CMUHinglishDoG.zip": {"num_bytes": 586961, "checksum": "2bb5cee3c7ca60e2e2ed25e2775e4025790623fe079d2e9d1831fbf6f6fc8086"}}, "download_size": 8749685, "post_processing_size": null, "dataset_size": 3890645, "size_in_bytes": 12640330}}
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