Create README.md

README.md

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+---
+annotations_creators:
+- machine-generated
+language_creators:
+- found
+multilinguality:
+- monolingual
+size_categories:
+- 100K<n<1M
+source_datasets:
+- extended
+task_categories:
+  - conversational
+  - text-generation
+  - text2text-generation
+language:
+- bn
+license:
+- cc-by-nc-sa-4.0
+---
+
+# Dataset Card for `dailydialogue_bn`
+
+## Table of Contents
+- [Dataset Card for `dailydialogue_bn`](#dataset-card-for-dailydialogue_bn)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+    - [Usage](#usage)
+  - [Dataset Structure](#dataset-structure)
+    - [Data Instances](#data-instances)
+    - [Data Fields](#data-fields)
+    - [Data Splits](#data-splits)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+    - [Annotations](#annotations)
+      - [Annotation process](#annotation-process)
+      - [Who are the annotators?](#who-are-the-annotators)
+    - [Personal and Sensitive Information](#personal-and-sensitive-information)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+  - [Additional Information](#additional-information)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+    - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Repository:** [https://github.com/csebuetnlp/BanglaNLG](https://github.com/csebuetnlp/BanglaNLG)
+- **Paper:** [**"BanglaBERT: Combating Embedding Barrier in Multilingual Models for Low-Resource Language Understanding"**](https://arxiv.org/abs/2101.00204)
+- **Point of Contact:** [Tahmid Hasan](mailto:[email protected])
+
+### Dataset Summary
+
+This is a Multi-turn dialogue dataset for Bengali, curated from the original English [DailyDialogue]() dataset and using the state-of-the-art English to Bengali translation model introduced **[here](https://aclanthology.org/2020.emnlp-main.207/).**
+
+
+### Supported Tasks and Leaderboards
+
+[More information needed](https://github.com/csebuetnlp/BanglaNLG)
+
+### Languages
+
+* `Bengali`
+
+### Usage
+```python
+from datasets import load_dataset
+dataset = load_dataset("csebuetnlp/dailydialogue_bn")
+```
+## Dataset Structure
+
+### Data Instances
+
+One example from the dataset is given below in JSON format. Each element of the `dialogue` feature represents a single turn of the conversation.
+  ```
+  {
+    "id": "130",
+    "dialogue": 
+    [
+        "তোমার জন্মদিনের জন্য তুমি কি করবে?",
+        "আমি আমার বন্ধুদের সাথে পিকনিক করতে চাই, মা।",
+        "বাড়িতে পার্টি হলে কেমন হয়? এভাবে আমরা একসাথে হয়ে উদযাপন করতে পারি।",
+        "ঠিক আছে, মা। আমি আমার বন্ধুদের বাড়িতে আমন্ত্রণ জানাবো।"
+    ]
+  }
+  ```
+
+### Data Fields
+
+The data fields are as follows:
+
+- `id`: a `string` feature.
+- `dialogue`: a List of `string` feature.
+
+
+### Data Splits
+|   split   |count  |
+|----------|--------|
+|`train`|  127771 |
+|`validation`| 2502  |
+|`test`| 2504 |
+
+
+
+
+## Dataset Creation
+
+For the training set, we translated the complete [DailyDialogue](https://aclanthology.org/N18-1101/) dataset using the English to Bangla translation model introduced [here](https://aclanthology.org/2020.emnlp-main.207/). Due to the possibility of incursions of error during automatic translation, we used the [Language-Agnostic BERT Sentence Embeddings (LaBSE)](https://arxiv.org/abs/2007.01852) of the translations and original sentences to compute their similarity. A datapoint was accepted if all of its constituent sentences had a similarity score over 0.7. 
+
+### Curation Rationale
+
+[More information needed](https://github.com/csebuetnlp/BanglaNLG)
+
+### Source Data
+
+[DailyDialogue](https://arxiv.org/abs/1606.05250)
+
+#### Initial Data Collection and Normalization
+
+[More information needed](https://github.com/csebuetnlp/BanglaNLG)
+
+
+#### Who are the source language producers?
+
+[More information needed](https://github.com/csebuetnlp/BanglaNLG)
+
+
+### Annotations
+
+[More information needed](https://github.com/csebuetnlp/BanglaNLG)
+
+
+#### Annotation process
+
+[More information needed](https://github.com/csebuetnlp/BanglaNLG)
+
+#### Who are the annotators?
+
+[More information needed](https://github.com/csebuetnlp/BanglaNLG)
+
+### Personal and Sensitive Information
+
+[More information needed](https://github.com/csebuetnlp/BanglaNLG)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More information needed](https://github.com/csebuetnlp/BanglaNLG)
+
+### Discussion of Biases
+
+[More information needed](https://github.com/csebuetnlp/BanglaNLG)
+
+### Other Known Limitations
+
+[More information needed](https://github.com/csebuetnlp/BanglaNLG)
+
+## Additional Information
+
+### Dataset Curators
+
+[More information needed](https://github.com/csebuetnlp/BanglaNLG)
+
+### Licensing Information
+
+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.
+### Citation Information
+
+If you use the dataset, please cite the following paper:
+```
+@inproceedings{bhattacharjee-etal-2023-banglanlg,
+    title = "{B}angla{NLG} and {B}angla{T}5: Benchmarks and Resources for Evaluating Low-Resource Natural Language Generation in {B}angla",
+    author = "Bhattacharjee, Abhik  and
+      Hasan, Tahmid  and
+      Ahmad, Wasi Uddin  and
+      Shahriyar, Rifat",
+    booktitle = "Findings of the Association for Computational Linguistics: EACL 2023",
+    month = may,
+    year = "2023",
+    address = "Dubrovnik, Croatia",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2023.findings-eacl.54",
+    pages = "726--735",
+    abstract = "This work presents {`}BanglaNLG,{'} a comprehensive benchmark for evaluating natural language generation (NLG) models in Bangla, a widely spoken yet low-resource language. We aggregate six challenging conditional text generation tasks under the BanglaNLG benchmark, introducing a new dataset on dialogue generation in the process. Furthermore, using a clean corpus of 27.5 GB of Bangla data, we pretrain {`}BanglaT5{'}, a sequence-to-sequence Transformer language model for Bangla. BanglaT5 achieves state-of-the-art performance in all of these tasks, outperforming several multilingual models by up to 9{\%} absolute gain and 32{\%} relative gain. We are making the new dialogue dataset and the BanglaT5 model publicly available at https://github.com/csebuetnlp/BanglaNLG in the hope of advancing future research on Bangla NLG.",
+}
+```
+
+
+### Contributions
+
+Thanks to [@abhik1505040](https://github.com/abhik1505040) and [@Tahmid](https://github.com/Tahmid04) for adding this dataset.