# Datasets: bigscience /open_subtitles_monolingual

 1 --- 2 annotations_creators: 3 - machine-generated 4 language_creators: 5 - found 6 languages: 7 - fr 8 - en 9 - zh-CN 10 - pt 11 - es 12 - ar 13 licenses: 14 - unknown 15 multilinguality: 16 - multilingual 17 pretty_name: '' 18 size_categories: 19 - unknown 20 source_datasets: 21 - original 22 task_categories: 23 - sequence-modeling 24 task_ids: 25 - language-modeling 26 --- 27 28 # Dataset Card Creation Guide 29 30 ## Table of Contents 31 - [Dataset Card Creation Guide](#dataset-card-creation-guide) 32 - [Table of Contents](#table-of-contents) 33 - [Dataset Description](#dataset-description) 34 - [Dataset Summary](#dataset-summary) 35 - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) 36 - [Languages](#languages) 37 - [Dataset Structure](#dataset-structure) 38 - [Data Instances](#data-instances) 39 - [Data Fields](#data-fields) 40 - [Data Splits](#data-splits) 41 - [Dataset Creation](#dataset-creation) 42 - [Curation Rationale](#curation-rationale) 43 - [Source Data](#source-data) 44 - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization) 45 - [Who are the source language producers?](#who-are-the-source-language-producers) 46 - [Citation Information](#citation-information) 47 - [Contributions](#contributions) 48 49 ## Dataset Description 50 51 - **Homepage:** [Opus OpenSubtitles](https://opus.nlpl.eu/OpenSubtitles-v2018.php) 52 - **Repository:** [If the dataset is hosted on github or has a github homepage, add URL here]() 53 - **Paper:** [OpenSubtitles2016: Extracting Large Parallel Corpora from Movie and TV Subtitles](http://www.lrec-conf.org/proceedings/lrec2016/pdf/947_Paper.pdf) 54 - **Leaderboard:** [If the dataset supports an active leaderboard, add link here]() 55 - **Point of Contact:** [If known, name and email of at least one person the reader can contact for questions about the dataset.]() 56 57 ### Dataset Summary 58 59 This is a new collection of translated movie subtitles from [http://www.opensubtitles.org/](http://www.opensubtitles.org/). 60 **IMPORTANT**: If you use the OpenSubtitle corpus: Please, add a link to [http://www.opensubtitles.org/](http://www.opensubtitles.org/) to your website and to your reports and publications produced with the data! 61 This is a slightly cleaner version of the subtitle collection using improved sentence alignment and better language checking. 62 62 languages, 1,782 bitexts 63 total number of files: 3,735,070 64 total number of tokens: 22.10G 65 total number of sentence fragments: 3.35G 66 67 This dataset only focus on monolingual subtitles with each document corresponding to a subtitle file. 68 69 ### Supported Tasks and Leaderboards 70 71 For each of the tasks tagged for this dataset, give a brief description of the tag, metrics, and suggested models (with a link to their HuggingFace implementation if available). Give a similar description of tasks that were not covered by the structured tag set (repace the task-category-tag with an appropriate other:other-task-name). 72 73 - task-category-tag: The dataset can be used to train a model for [TASK NAME], which consists in [TASK DESCRIPTION]. Success on this task is typically measured by achieving a *high/low* [metric name](https://huggingface.co/metrics/metric_name). The ([model name](https://huggingface.co/model_name) or [model class](https://huggingface.co/transformers/model_doc/model_class.html)) model currently achieves the following score. *[IF A LEADERBOARD IS AVAILABLE]:* This task has an active leaderboard which can be found at [leaderboard url]() and ranks models based on [metric name](https://huggingface.co/metrics/metric_name) while also reporting [other metric name](https://huggingface.co/metrics/other_metric_name). 74 75 ### Languages 76 77 Provide a brief overview of the languages represented in the dataset. Describe relevant details about specifics of the language such as whether it is social media text, African American English,... 78 79 When relevant, please provide [BCP-47 codes](https://tools.ietf.org/html/bcp47), which consist of a [primary language subtag](https://tools.ietf.org/html/bcp47#section-2.2.1), with a [script subtag](https://tools.ietf.org/html/bcp47#section-2.2.3) and/or [region subtag](https://tools.ietf.org/html/bcp47#section-2.2.4) if available. 80 81 ## Dataset Structure 82 83 ### Data Instances 84 85 Each example corresponds to a subtitle file. 86 87  88 { 89 "subtitle": "Happy birthday to you."\n"Happy birthday to you."\n"Happy birthday, dear..."\nMemory is always there.\n17 years old,\nI was young, vulnerable, and powerless, making the same mistakes over and over again.\nAnd yet she was strong.\nBut that is always where my memory ends.\nAt that place, when we were 17.\nAnd as it ends there, my life also comes to a stop.\n"We Were There\n- Last Part " ...., 90 "meta": { 91 "year": 2012, 92 "imdbId": 2194724, 93 "subtitleId": 4786461.xml, 94 } 95 } 96  97 98 ### Data Fields 99 100 Each example includes the text in the subtitle entry as well as meta data. 101 102 - subtitle: The subtitle text. The punctuation includes escaped line breaks characters. 103 - year: Year the subtitle file was added. 104 - imdbId: Movie unique identifier following the reference from [Internet Movie Database](http://www.imdb.com) 105 - subtitleId: Subtitle file identifier. They may be multiple examples refering to the same movie for a given language. 106 107 ### Data Splits 108 109 The dataset is split given languages. 110 111 | Language | Number of documents | Average document length | Total Number of tokens | File size | 112 | -------- | --------------------- | ----------------------- | ---------------------- | --------- | 113 | fr | 120,000 | 5,002 | 600M | 1.1G | 114 | en | 440,000 | 5,575 | 2,453M | 3.5G | 115 | zh-CN | 20,000 | 2,168 | 43M | 269M | 116 | pt | 130,000 | 4,932 | 641M | 1.2G | 117 | es | 230,000 | 5,020 | 1,155M | 2.2G | 118 | ar | 90,000 | 4,379 | 394M | 1.3G | 119 120 ## Dataset Creation 121 122 ### Curation Rationale 123 124 What need motivated the creation of this dataset? What are some of the reasons underlying the major choices involved in putting it together? 125 126 ### Source Data 127 128 The dataset is based on [OpenSubtitles](http://www.opensubtitles.org) database. 129 130 #### Initial Data Collection and Normalization 131 132 Raw subtitle files follow a series of pre-precessing operations: 133 - Subtitle conversion: First the encoding is detected and converted to utf-8. 134 - Sentence segmentation and tokenisation: Sentences are then reconstructed since raw subtitle files corresponds to block of text which do not align with sentence boundaries. Sentence are then tokenized whith specific tools for Japanese and Chinese and the default Moses tokenizer otherwise. 135 - Correction of OCR and spelling errors: Some subtitles are automatically generated using Optical Character Recognition (OCR). This leads to recuring errors which are automatically detected and corrected using statistical language model. 136 - Inclusion of meta-data: Each file is associated with meta-data. 137 - Post-processing: In the current dataset, we add some basic post-processing steps. We parsed the xmlfiles and untokenize the sentences. 138 139 #### Who are the source language producers? 140 141 Subtitles are written by contributors of the [OpenSubtitles](http://www.opensubtitles.org) database. They may be human written or automatically generated using OCR methods. 142 143 ### Citation Information 144 145  146 @inproceedings{lison_16, 147 author = {Pierre Lison and 148 J{\"{o}}rg Tiedemann}, 149 editor = {Nicoletta Calzolari and 150 Khalid Choukri and 151 Thierry Declerck and 152 Sara Goggi and 153 Marko Grobelnik and 154 Bente Maegaard and 155 Joseph Mariani and 156 H{\'{e}}l{\{e}}ne Mazo and 157 Asunci{\'{o}}n Moreno and 158 Jan Odijk and 159 Stelios Piperidis}, 160 title = {OpenSubtitles2016: Extracting Large Parallel Corpora from Movie and 161 {TV} Subtitles}, 162 booktitle = {Proceedings of the Tenth International Conference on Language Resources 163 and Evaluation {LREC} 2016, Portoro{\v{z}}, Slovenia, May 23-28, 2016}, 164 publisher = {European Language Resources Association {(ELRA)}}, 165 year = {2016}, 166 url = {http://www.lrec-conf.org/proceedings/lrec2016/summaries/947.html}, 167 } 168 ` 169 170 171 ### Contributions 172 173 Thanks to [@AntoineSimoulin](https://github.com/AntoineSimoulin) for adding this dataset. 174