Update README.md

README.md

@@ -19,9 +19,9 @@ It was created from the CEFC-Orféo corpus. This dataset was presented in the re
 Propicto-orféo contains three CSV files : train, valid and test, with the following statistics :
 | **Split** | **Number of utterances** |
 |:-----------:|:-----------------------:|
-| train |  |
-| valid |  |
-| test |  |
+| train | 231 374 |
+| valid | 28 796 |
+| test | 29 009 |
 
 - **Curated by:** Cécile MACAIRE
 - **Funded by :** [PROPICTO ANR-20-CE93-0005](https://anr.fr/Projet-ANR-20-CE93-0005)
@@ -34,13 +34,28 @@ Each file contains the following information :
 ```csv
 id : the unique identifier of the utterance, which corresponds to a unique audio clip file (in wav) for the orféo dataset
 text : the transcription of the audio clip
-pictos : the sequence of id pictograms from [ARASAAC](https://arasaac.org/)
-tokens : the sequence of tokens, each of them is the keyword associated to the ARASAAC id pictogram.
+pictos : the sequence of id pictograms from ARASAAC
+tokens : the sequence of tokens, each of them is the keyword associated to the ARASAAC id pictogram
 ```
 
-## Dataset Sources [optional]
+## Dataset example
 
-<!-- Provide the basic links for the dataset. -->
+For the given sample :
+```csv
+id : cefc-cfpb-1000-5-1186
+text : tu essayes de mélanger les deux
+pictos : [6625, 26144, 7074, 5515, 5367]
+tokens : toi essayer de mélanger à_côté_de
+```
+
+The clip is from the Orféo subcorpus [CFPB, 1000-5](https://orfeo.ortolang.fr/annis-sample/cfpb/CFPB-1000-5.html), with the sentence ID 1186.
+The text is the associated transcription, in en : “you try to mix the two”.
+Pictos is the sequence of pictogram IDs, each of them can be retrieved from here : 6625 = https://static.arasaac.org/pictograms/**6625**/**6625**_2500.png
+Tokens are retrieved from a specific lexicon and can be used to train translation models.
+
+![]()
+
+## Dataset Sources
 
 - **Repository:** [CEFC-Orféo](https://www.ortolang.fr/market/corpora/cefc-orfeo)
 - **Papers :**
@@ -49,68 +64,22 @@ tokens : the sequence of tokens, each of them is the keyword associated to the A
 
 ## Uses
 
-<!-- Address questions around how the dataset is intended to be used. -->
-
-### Direct Use
-
-<!-- This section describes suitable use cases for the dataset. -->
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
-
+Propicto-orféo is intended to be used to train Speech-to-Pictograms translation and Text-to-Pictograms translation models. 
+This dataset can also be used to fine-tune large language models to perform translation into pictograms. 
 
 ## Dataset Creation
 
-### Curation Rationale
-
-<!-- Motivation for the creation of this dataset. -->
-
-[More Information Needed]
-
-### Source Data
-
-<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
-
-#### Data Collection and Processing
-
-<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
-
-[More Information Needed]
-
-#### Who are the source data producers?
-
-<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
-
-[More Information Needed]
-
-### Annotations [optional]
-
-<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
-
-#### Annotation process
-
-<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
-
-[More Information Needed]
+The dataset is created by applying a specific formalism that converts french oral transcriptions into a corresponding sequence of pictograms.
+The formalism includes a set of grammatical rules to handle specific phenomenon (negation, name entities, pronominal form, plural, ...) to the French language, as well as a dictionary which associates each ARASAAC ID pictogram with a set of keywords (tokens).
+This formalism was presented at [LREC](https://aclanthology.org/2024.lrec-main.76/).
 
-#### Who are the annotators?
-
-<!-- This section describes the people or systems who created the annotations. -->
-
-[More Information Needed]
-
-#### Personal and Sensitive Information
-
-<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
-
-[More Information Needed]
+Source Data : conversations / meetings / daily life situations (oral transcriptions)
 
 ## Bias, Risks, and Limitations
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+The translation 
+
 
-[More Information Needed]
 
 ### Recommendations