Update README.md

README.md

@@ -23,9 +23,279 @@ language:
 - ta
 - te
 - ur
+language_details: >-
+  asm_Beng, ben_Beng, brx_Deva, doi_Deva, eng_Latn, gom_Deva, guj_Gujr,
+  hin_Deva, kan_Knda, kas_Arab, mai_Deva, mal_Mlym, mar_Deva, mni_Mtei, 
+  npi_Deva, ory_Orya, pan_Guru, san_Deva, sat_Olck, snd_Deva, tam_Taml, 
+  tel_Telu, urd_Arab
+license: cc-by-4.0
+language_creators:
+- expert-generated
+multilinguality:
+- multilingual
+- translation
+pretty_name: in22-conv
+size_categories:
+- 1K<n<10K
+task_categories:
+- translation
 configs:
   - config_name: default
     data_files:
       - split: test
         path: test.parquet
----
+---
+
+# IN22-Conv
+
+IN-22 is a newly created comprehensive benchmark for evaluating machine translation performance in multi-domain, n-way parallel contexts across 22 Indic languages. IN22-Conv is the conversation domain subset of IN22. It is designed to assess translation quality in typical day-to-day conversational-style applications. The evaluation subset consists of 1503 sentences translated across 22 Indic languages enabling evaluation of MT systems across 506 directions.
+
+Currently, we use it for sentence-level evaluation of MT systems but it can be repurposed for document translation evaluation as well.
+
+Here is the domain distribution of our IN22-Conv evaluation subset.
+
+<table style="width:25%">
+    <tr>
+        <td>domain</td>
+        <td>count</td>
+    </tr>
+    <tr>
+        <td>hobbies</td>
+        <td>120</td>
+    </tr>
+    <tr>
+        <td>daily_dialogue</td>
+        <td>117</td>
+    </tr>
+    <tr>
+        <td>government</td>
+        <td>116</td>
+    </tr>
+    <tr>
+        <td>geography</td>
+        <td>114</td>
+    </tr>
+    <tr>
+        <td>sports</td>
+        <td>100</td>
+    </tr>
+    <tr>
+        <td>entertainment</td>
+        <td>97</td>
+    </tr>
+    <tr>
+        <td>history</td>
+        <td>97</td>
+    </tr>
+    <tr>
+        <td>legal</td>
+        <td>96</td>
+    </tr>
+    <tr>
+        <td>arts</td>
+        <td>95</td>
+    </tr>
+    <tr>
+        <td>college_life</td>
+        <td>94</td>
+    </tr>
+    <tr>
+        <td>tourism</td>
+        <td>91</td>
+    </tr>
+    <tr>
+        <td>school_life</td>
+        <td>87</td>
+    </tr>
+    <tr>
+        <td>insurance</td>
+        <td>82</td>
+    </tr>
+    <tr>
+        <td>culture</td>
+        <td>73</td>
+    </tr>
+    <tr>
+        <td>healthcare</td>
+        <td>67</td>
+    </tr>
+    <tr>
+        <td>banking</td>
+        <td>57</td>
+    </tr>
+    <tr>
+        <td>total</td>
+        <td>1503</td>
+    </tr>
+</table>
+
+Please refer to the `Appendix E: Dataset Card` of the [preprint](https://arxiv.org/abs/2305.16307) on detailed description of dataset curation, annotation and quality control process.
+
+
+### Dataset Structure
+
+#### Dataset Fields
+
+- `id`: Row number for the data entry, starting at 1.
+- `doc_id`: Unique identifier of the conversation.
+- `sent_id`: Unique identifier of the sentence order in each conversation.
+- `topic`: The specific topic of the conversation within the domain.
+- `domain`: The domain of the conversation.
+- `prompt`: The prompt provided to annotators to simulate the conversation.
+- `scenario`: The scenario or context in which the conversation takes place.
+- `speaker`: The speaker identifier in the conversation.
+- `turn`: The turn within the conversation.
+
+#### Data Instances
+
+A sample from the `gen` split for the English language (`eng_Latn` config) is provided below. All configurations have the same structure, and all sentences are aligned across configurations and splits.
+
+```python
+{
+   "id": 1,
+   "doc_id": 0,
+   "sent_id": 1,
+   "topic": "Festivities",
+   "domain": "culture",
+   "prompt": "14th April a holiday",
+   "scenario": "Historical importance",
+   "speaker": 1,
+   "turn": 1,
+   "sentence": "Mom, let's go for a movie tomorrow."
+}
+```
+
+When using a hyphenated pairing or using the `all` function, data will be presented as follows:
+
+```python
+{
+   "id": 1,
+   "doc_id": 0,
+   "sent_id": 1,
+   "topic": "Festivities",
+   "domain": "culture",
+   "prompt": "14th April a holiday",
+   "scenario": "Historical importance",
+   "speaker": 1,
+   "turn": 1,
+   "sentence_eng_Latn": "Mom, let's go for a movie tomorrow.",
+   "sentence_hin_Deva": "माँ, चलो कल एक फिल्म देखने चलते हैं।"
+}
+```
+
+#### Sample Conversation
+
+<table>
+    <tr>
+        <td>Speaker</td>
+        <td>Turn</td>
+    </tr>
+    <tr>
+        <td>Speaker 1</td>
+        <td>Mom, let&#39;s go for a movie tomorrow. I don&#39;t have to go to school. It is a holiday.</td>
+    </tr>
+    <tr>
+        <td>Speaker 2</td>
+        <td>Oh, tomorrow is the 14th of April right? Your dad will also have the day off from work. We can make a movie plan!</td>
+    </tr>
+    <tr>
+        <td>Speaker 1</td>
+        <td>That&#39;s a good news! Why is it a holiday though? Are all schools, colleges and offices closed tomorrow?</td>
+    </tr>
+    <tr>
+        <td>Speaker 2</td>
+        <td>It is Ambedkar Jayanti tomorrow! This day is celebrated annually to mark the birth of Dr. B. R Ambedkar. Have you heard of him?</td>
+    </tr>
+    <tr>
+        <td>Speaker 1</td>
+        <td>I think I have seen him in my History and Civics book. Is he related to our Constitution?</td>
+    </tr>
+    <tr>
+        <td>Speaker 2</td>
+        <td>Absolutely! He is known as the father of the Indian Constitution. He was a civil rights activist who played a major role in formulating the Constitution. He played a crucial part in shaping the vibrant democratic structure that India prides itself upon.</td>
+    </tr>
+    <tr>
+        <td></td>
+        <td>...</td>
+    </tr>
+</table>
+
+
+### Usage Instructions
+
+```python
+from datasets import load_dataset
+
+# download and load all the pairs
+dataset = load_dataset("ai4bharat/IN22-Conv", "all")
+
+# download and load specific pairs
+dataset = load_dataset("ai4bharat/IN22-Conv", "eng_Latn-hin_Deva")
+```
+
+### Languages Covered
+
+<table style="width: 40%">
+    <tr>
+        <td>Assamese (asm_Beng)</td>
+        <td>Kashmiri (Arabic) (kas_Arab)</td>
+        <td>Punjabi (pan_Guru)</td>
+    </tr>
+    <tr>
+        <td>Bengali (ben_Beng)</td>
+        <td>Kashmiri (Devanagari) (kas_Deva)</td>
+        <td>Sanskrit (san_Deva)</td>
+    </tr>
+    <tr>
+        <td>Bodo (brx_Deva)</td>
+        <td>Maithili (mai_Deva)</td>
+        <td>Santali (sat_Olck)</td>
+    </tr>
+    <tr>
+        <td>Dogri (doi_Deva)</td>
+        <td>Malayalam (mal_Mlym)</td>
+        <td>Sindhi (Arabic) (snd_Arab)</td>
+    </tr>
+    <tr>
+        <td>English (eng_Latn)</td>
+        <td>Marathi (mar_Deva)</td>
+        <td>Sindhi (Devanagari) (snd_Deva)</td>
+    </tr>
+    <tr>
+        <td>Konkani (gom_Deva)</td>
+        <td>Manipuri (Bengali) (mni_Beng)</td>
+        <td>Tamil (tam_Taml)</td>
+    </tr>
+    <tr>
+        <td>Gujarati (guj_Gujr)</td>
+        <td>Manipuri (Meitei) (mni_Mtei)</td>
+        <td>Telugu (tel_Telu)</td>
+    </tr>
+    <tr>
+        <td>Hindi (hin_Deva)</td>
+        <td>Nepali (npi_Deva)</td>
+        <td>Urdu (urd_Arab)</td>
+    </tr>
+    <tr>
+        <td>Kannada (kan_Knda)</td>
+        <td>Odia (ory_Orya)</td>
+    </tr>
+</table>
+
+
+### Citation
+
+If you consider using our work then please cite using:
+
+```
+@article{gala2023indictrans,
+title={IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian Languages},
+author={Jay Gala and Pranjal A Chitale and A K Raghavan and Varun Gumma and Sumanth Doddapaneni and Aswanth Kumar M and Janki Atul Nawale and Anupama Sujatha and Ratish Puduppully and Vivek Raghavan and Pratyush Kumar and Mitesh M Khapra and Raj Dabre and Anoop Kunchukuttan},
+journal={Transactions on Machine Learning Research},
+issn={2835-8856},
+year={2023},
+url={https://openreview.net/forum?id=vfT4YuzAYA},
+note={}
+}
+```
+