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  license: mit
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  license: mit
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+ language:
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+ - fr
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+ task_categories:
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+ - image-to-text
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+ pretty_name: PyLaia RIMES
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+
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+ dataset_info:
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+ features:
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+ - name: image
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+ dtype: image
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+ - name: text
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+ dtype: string
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+ splits:
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+ - name: train
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+ num_examples: 10188
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+ - name: validation
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+ num_examples: 1138
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+ - name: test
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+ num_examples: 778
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+ dataset_size: 12104
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  ---
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+
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+ # PyLaia RIMES Dataset
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+
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+ ## Table of Contents
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+ - [PyLaia RIMES Dataset](#pylaia-rimes-dataset)
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+ - [Table of Contents](#table-of-contents)
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+ - [Dataset Description](#dataset-description)
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+ - [Dataset Summary](#dataset-summary)
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+ - [Languages](#languages)
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+ - [Dataset Structure](#dataset-structure)
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+ - [Data Instances](#data-instances)
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+ - [Data Fields](#data-fields)
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+ - [Data Splits](#data-splits)
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+
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+ ## Dataset Description
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+
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+ - **Homepage:** [ARTEMIS](https://artemis.telecom-sudparis.eu/2012/10/05/rimes/)
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+ - **PapersWithCode:** [Papers using the RIMES dataset](https://paperswithcode.com/dataset/rimes)
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+ - **Point of Contact:** [TEKLIA](https://teklia.com)
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+
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+ ### Dataset Summary
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+
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+ Briefly summarize the dataset, its intended use and the supported tasks. Give an overview of how and why the dataset was created. The summary should explicitly mention the **languages** present in the dataset (possibly in broad terms, e.g. *translations between several pairs of European languages*), and describe the domain, topic, or genre covered.
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+
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+ ### Languages
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+
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+ All the documents in the dataset are written in French.
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+
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+ ## Dataset Structure
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+
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+ ### Data Instances
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+
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+ ```
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+ {
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+ 'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=2560x128 at 0x1A800E8E190,
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+ 'text': 'Comme indiqué dans les conditions particulières de mon contrat d'assurance'
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+ }
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+ ```
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+
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+ ### Data Fields
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+
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+
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+ - `image`: A PIL.Image.Image object containing the image. Note that when accessing the image column: dataset[0]["image"] the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the "image" column, i.e. dataset[0]["image"] should always be preferred over dataset["image"][0].
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+ - `text`: the label transcription of the image.
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+
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+ ### Data Splits
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+
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+ Describe and name the splits in the dataset if there are more than one.
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+
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+ Describe any criteria for splitting the data, if used. If there are differences between the splits (e.g. if the training annotations are machine-generated and the dev and test ones are created by humans, or if different numbers of annotators contributed to each example), describe them here.
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+
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+ Provide the sizes of each split. As appropriate, provide any descriptive statistics for the features, such as average length. For example:
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+
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+ | | train | validation | test |
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+ |-------------------------|------:|-----------:|-----:|
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+ | Input Sentences | | | |
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+ | Average Sentence Length | | | |
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