--- dataset_info: features: - name: domain dtype: string - name: source_language dtype: string - name: target_language dtype: string - name: source_text dtype: string - name: target_text dtype: string splits: - name: train num_bytes: 381941890 num_examples: 745805 download_size: 136942400 dataset_size: 381941890 configs: - config_name: default data_files: - split: train path: data/train-* license: cc-by-nc-4.0 language: - hi - te --- # Dataset Card for Dataset Name The-LTRC-Hindi-Telugu-Parallel-Corpus ## Dataset Description - Contains Human post edited parallel corpora for Hindi and Telugu ### Dataset Size and Domains 506178 parallel sentences for Chemistry, Law, News & General, HealthCare, Education Others, open education books ## Dataset Structure - File name contains source language and target language based on train and test splits - {'domain', 'source_language', 'target_language', 'source_text', 'target_text'} ### Source Data Educational Lectures ### Details - **Curated by:** LTRC, IIIT Hyderabad, India - **Funded by:** MEITY, GOI, India - **Shared by:** MT-NLP, LTRC, IIIT Hyderabad, India - **Language(s) (NLP):** tel_Telu, hin_Deva - **Paper:** The LTRC Hindi-Telugu Parallel Corpus; Vandan Mujadia, Dipti Sharma ### Project Investigator - Prof. Dipti Misra Sharma, LTRC, IIIT Hyderabad #### Data Curators - LTRC Language Experts **BibTeX:** ``` @inproceedings{mujadia-sharma-2022-ltrc, title = "The {LTRC} {H}indi-{T}elugu Parallel Corpus", author = "Mujadia, Vandan and Sharma, Dipti", editor = "Calzolari, Nicoletta and B{\'e}chet, Fr{\'e}d{\'e}ric and Blache, Philippe and Choukri, Khalid and Cieri, Christopher and Declerck, Thierry and Goggi, Sara and Isahara, Hitoshi and Maegaard, Bente and Mariani, Joseph and Mazo, H{\'e}l{\`e}ne and Odijk, Jan and Piperidis, Stelios", booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference", month = jun, year = "2022", address = "Marseille, France", publisher = "European Language Resources Association", url = "https://aclanthology.org/2022.lrec-1.365", pages = "3417--3424", abstract = "We present the Hindi-Telugu Parallel Corpus of different technical domains such as Natural Science, Computer Science, Law and Healthcare along with the General domain. The qualitative corpus consists of 700K parallel sentences of which 535K sentences were created using multiple methods such as extract, align and review of Hindi-Telugu corpora, end-to-end human translation, iterative back-translation driven post-editing and around 165K parallel sentences were collected from available sources in the public domain. We present the comparative assessment of created parallel corpora for representativeness and diversity. The corpus has been pre-processed for machine translation, and we trained a neural machine translation system using it and report state-of-the-art baseline results on the developed development set over multiple domains and on available benchmarks. With this, we define a new task on Domain Machine Translation for low resource language pairs such as Hindi and Telugu. The developed corpus (535K) is freely available for non-commercial research and to the best of our knowledge, this is the well curated, largest, publicly available domain parallel corpus for Hindi-Telugu.", } ``` ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]