abhik1505040 commited on
Commit
3038cb1
1 Parent(s): eb7cf39

Create README.md

Browse files
Files changed (1) hide show
  1. README.md +202 -0
README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ annotations_creators:
3
+ - other
4
+ language:
5
+ - bn
6
+ - en
7
+ language_creators:
8
+ - found
9
+ license:
10
+ - cc-by-nc-sa-4.0
11
+ multilinguality:
12
+ - translation
13
+ pretty_name: BanglaNMT
14
+ size_categories:
15
+ - 1M<n<10M
16
+ source_datasets: []
17
+ tags:
18
+ - bengali
19
+ - BanglaNMT
20
+ task_categories:
21
+ - translation
22
+ ---
23
+
24
+ # Dataset Card for `BanglaNMT`
25
+
26
+ ## Table of Contents
27
+ - [Dataset Card for `BanglaNMT`](#dataset-card-for-BanglaNMT)
28
+ - [Table of Contents](#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
+ - [Usage](#usage)
34
+ - [Dataset Structure](#dataset-structure)
35
+ - [Data Instances](#data-instances)
36
+ - [Data Fields](#data-fields)
37
+ - [Data Splits](#data-splits)
38
+ - [Dataset Creation](#dataset-creation)
39
+ - [Curation Rationale](#curation-rationale)
40
+ - [Source Data](#source-data)
41
+ - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
42
+ - [Who are the source language producers?](#who-are-the-source-language-producers)
43
+ - [Annotations](#annotations)
44
+ - [Annotation process](#annotation-process)
45
+ - [Who are the annotators?](#who-are-the-annotators)
46
+ - [Personal and Sensitive Information](#personal-and-sensitive-information)
47
+ - [Considerations for Using the Data](#considerations-for-using-the-data)
48
+ - [Social Impact of Dataset](#social-impact-of-dataset)
49
+ - [Discussion of Biases](#discussion-of-biases)
50
+ - [Other Known Limitations](#other-known-limitations)
51
+ - [Additional Information](#additional-information)
52
+ - [Dataset Curators](#dataset-curators)
53
+ - [Licensing Information](#licensing-information)
54
+ - [Citation Information](#citation-information)
55
+ - [Contributions](#contributions)
56
+
57
+ ## Dataset Description
58
+
59
+ - **Repository:** [https://github.com/csebuetnlp/banglanmt](https://github.com/csebuetnlp/banglanmt)
60
+ - **Paper:** [**"Not Low-Resource Anymore: Aligner Ensembling, Batch Filtering, and New Datasets for Bengali-English Machine Translation"**](https://www.aclweb.org/anthology/2020.emnlp-main.207)
61
+ - **Point of Contact:** [Tahmid Hasan](mailto:tahmidhasan@cse.buet.ac.bd)
62
+
63
+ ### Dataset Summary
64
+
65
+ This is the largest Machine Translation (MT) dataset for Bengali-English, curated using novel sentence alignment methods introduced **[here](https://aclanthology.org/2020.emnlp-main.207/).**
66
+
67
+ **Note:** This is a filtered version of the original dataset that the authors used for NMT training. For the complete set, refer to the offical [repository](https://github.com/csebuetnlp/banglanmt)
68
+
69
+
70
+ ### Supported Tasks and Leaderboards
71
+
72
+ [More information needed](https://github.com/csebuetnlp/banglanmt)
73
+
74
+ ### Languages
75
+
76
+ - `Bengali`
77
+ - `English`
78
+
79
+ ### Usage
80
+ ```python
81
+ from datasets import load_dataset
82
+ dataset = load_dataset("csebuetnlp/BanglaNMT")
83
+ ```
84
+ ## Dataset Structure
85
+
86
+ ### Data Instances
87
+
88
+ One example from the dataset is given below in JSON format.
89
+ ```
90
+ {
91
+ 'bn': 'বিমানবন্দরে যুক্তরাজ্যে নিযুক্ত বাংলাদেশ হাইকমিশনার সাঈদা মুনা তাসনীম ও লন্ডনে বাংলাদেশ মিশনের জ্যেষ্ঠ কর্মকর্তারা তাকে বিদায় জানান।', 'en': 'Bangladesh High Commissioner to the United Kingdom Saida Muna Tasneen and senior officials of Bangladesh Mission in London saw him off at the airport.'
92
+ }
93
+ ```
94
+
95
+ ### Data Fields
96
+
97
+ The data fields are as follows:
98
+
99
+ - `bn`: a `string` feature indicating the Bengali sentence.
100
+ - `en`: a `string` feature indicating the English translation.
101
+
102
+ ### Data Splits
103
+ | split |count |
104
+ |----------|--------|
105
+ |`train`| 2659723 |
106
+ |`validation`| 597 |
107
+ |`test`| 1000 |
108
+
109
+
110
+
111
+
112
+ ## Dataset Creation
113
+
114
+ [More information needed](https://github.com/csebuetnlp/banglanmt)
115
+
116
+ ### Curation Rationale
117
+
118
+ [More information needed](https://github.com/csebuetnlp/banglanmt)
119
+
120
+ ### Source Data
121
+
122
+ [More information needed](https://github.com/csebuetnlp/banglanmt)
123
+
124
+ #### Initial Data Collection and Normalization
125
+
126
+ [More information needed](https://github.com/csebuetnlp/banglanmt)
127
+
128
+
129
+ #### Who are the source language producers?
130
+
131
+ [More information needed](https://github.com/csebuetnlp/banglanmt)
132
+
133
+
134
+ ### Annotations
135
+
136
+ [More information needed](https://github.com/csebuetnlp/banglanmt)
137
+
138
+
139
+ #### Annotation process
140
+
141
+ [More information needed](https://github.com/csebuetnlp/banglanmt)
142
+
143
+ #### Who are the annotators?
144
+
145
+ [More information needed](https://github.com/csebuetnlp/banglanmt)
146
+
147
+ ### Personal and Sensitive Information
148
+
149
+ [More information needed](https://github.com/csebuetnlp/banglanmt)
150
+
151
+ ## Considerations for Using the Data
152
+
153
+ ### Social Impact of Dataset
154
+
155
+ [More information needed](https://github.com/csebuetnlp/banglanmt)
156
+
157
+ ### Discussion of Biases
158
+
159
+ [More information needed](https://github.com/csebuetnlp/banglanmt)
160
+
161
+ ### Other Known Limitations
162
+
163
+ [More information needed](https://github.com/csebuetnlp/banglanmt)
164
+
165
+ ## Additional Information
166
+
167
+ ### Dataset Curators
168
+
169
+ [More information needed](https://github.com/csebuetnlp/banglanmt)
170
+
171
+ ### Licensing Information
172
+
173
+ Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0)](https://creativecommons.org/licenses/by-nc-sa/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
174
+ ### Citation Information
175
+
176
+ If you use the dataset, please cite the following paper:
177
+ ```
178
+ @inproceedings{hasan-etal-2020-low,
179
+ title = "Not Low-Resource Anymore: Aligner Ensembling, Batch Filtering, and New Datasets for {B}engali-{E}nglish Machine Translation",
180
+ author = "Hasan, Tahmid and
181
+ Bhattacharjee, Abhik and
182
+ Samin, Kazi and
183
+ Hasan, Masum and
184
+ Basak, Madhusudan and
185
+ Rahman, M. Sohel and
186
+ Shahriyar, Rifat",
187
+ booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
188
+ month = nov,
189
+ year = "2020",
190
+ address = "Online",
191
+ publisher = "Association for Computational Linguistics",
192
+ url = "https://www.aclweb.org/anthology/2020.emnlp-main.207",
193
+ doi = "10.18653/v1/2020.emnlp-main.207",
194
+ pages = "2612--2623",
195
+ abstract = "Despite being the seventh most widely spoken language in the world, Bengali has received much less attention in machine translation literature due to being low in resources. Most publicly available parallel corpora for Bengali are not large enough; and have rather poor quality, mostly because of incorrect sentence alignments resulting from erroneous sentence segmentation, and also because of a high volume of noise present in them. In this work, we build a customized sentence segmenter for Bengali and propose two novel methods for parallel corpus creation on low-resource setups: aligner ensembling and batch filtering. With the segmenter and the two methods combined, we compile a high-quality Bengali-English parallel corpus comprising of 2.75 million sentence pairs, more than 2 million of which were not available before. Training on neural models, we achieve an improvement of more than 9 BLEU score over previous approaches to Bengali-English machine translation. We also evaluate on a new test set of 1000 pairs made with extensive quality control. We release the segmenter, parallel corpus, and the evaluation set, thus elevating Bengali from its low-resource status. To the best of our knowledge, this is the first ever large scale study on Bengali-English machine translation. We believe our study will pave the way for future research on Bengali-English machine translation as well as other low-resource languages. Our data and code are available at https://github.com/csebuetnlp/banglanmt.",
196
+ }
197
+ ```
198
+
199
+
200
+ ### Contributions
201
+
202
+ Thanks to [@abhik1505040](https://github.com/abhik1505040) and [@Tahmid](https://github.com/Tahmid04) for adding this dataset.