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Upload new dataset version

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  1. .gitattributes +2 -0
  2. README.md +15 -10
  3. ca-de_6M.ca +3 -0
  4. ca-de_6M.de +3 -0
  5. ca-de_6M.parquet +3 -0
.gitattributes CHANGED
@@ -56,3 +56,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  ca-de_all_2023_09_11.ca filter=lfs diff=lfs merge=lfs -text
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  ca-de_all_2023_09_11.de filter=lfs diff=lfs merge=lfs -text
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  ca-de_all_2023_09_11.tsv filter=lfs diff=lfs merge=lfs -text
 
 
 
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  ca-de_all_2023_09_11.ca filter=lfs diff=lfs merge=lfs -text
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  ca-de_all_2023_09_11.de filter=lfs diff=lfs merge=lfs -text
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  ca-de_all_2023_09_11.tsv filter=lfs diff=lfs merge=lfs -text
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+ ca-de_6M.ca filter=lfs diff=lfs merge=lfs -text
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+ ca-de_6M.de filter=lfs diff=lfs merge=lfs -text
README.md CHANGED
@@ -39,11 +39,10 @@ The sentences included in the dataset are in Catalan (CA) and German (DE).
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  Two separate txt files are provided with the sentences sorted in the same order:
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- - ca-de_all_2023_09_11.ca
 
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- - ca-de_all_2023_09_11.de
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-
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- The dataset is additionally provided in parquet format: ca-de_all_2023_09_11.parquet.
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  The parquet file contains two columns of parallel text obtained from the two original text files.
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  Each row in the file represents a pair of parallel sentences in the two languages of the dataset.
@@ -67,24 +66,30 @@ This dataset is aimed at promoting the development of Machine Translation betwee
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  #### Initial Data Collection and Normalization
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- The first portion of the corpus is a combination of the following original datasets collected from [Opus](https://opus.nlpl.eu/):
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  MultiCCAligned, WikiMatrix, GNOME, KDE4, OpenSubtitles, GlobalVoices, Tatoeba.
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  Additionally, the corpus contains synthetic parallel data generated from the original Spanish-Catalan Europarl and Tilde corpora
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  made public by [SoftCatalà](https://github.com/Softcatala/Europarl-catalan).
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  A last portion of the dataset is composed by synthetic parallel data generated from a random sampling of the Spanish-German corpora
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- available on [Opus](https://opus.nlpl.eu/) and translated into Catalan using the [PlanTL es-ca](https://huggingface.co/PlanTL-GOB-ES/mt-plantl-es-ca) model.
 
 
 
 
 
 
 
 
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- All datasets are deduplicated and filtered to remove any sentence pairs with a cosine similarity of less than 0.75.
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- This is done using sentence embeddings calculated using [LaBSE](https://huggingface.co/sentence-transformers/LaBSE).
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- The filtered datasets are then concatenated to form the final corpus.
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  #### Who are the source language producers?
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  [Opus](https://opus.nlpl.eu/)
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- [SoftCatalà](https://github.com/Softcatala/Europarl-catalan)
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  ### Annotations
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  Two separate txt files are provided with the sentences sorted in the same order:
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+ - ca-de_6M.ca
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+ - ca-de_6M.de
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+ The dataset is additionally provided in parquet format: ca-de_6M.parquet.
 
 
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  The parquet file contains two columns of parallel text obtained from the two original text files.
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  Each row in the file represents a pair of parallel sentences in the two languages of the dataset.
 
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  #### Initial Data Collection and Normalization
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+ <!-- The first portion of the corpus is a combination of the following original datasets collected from [Opus](https://opus.nlpl.eu/):
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  MultiCCAligned, WikiMatrix, GNOME, KDE4, OpenSubtitles, GlobalVoices, Tatoeba.
71
 
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  Additionally, the corpus contains synthetic parallel data generated from the original Spanish-Catalan Europarl and Tilde corpora
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  made public by [SoftCatalà](https://github.com/Softcatala/Europarl-catalan).
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  A last portion of the dataset is composed by synthetic parallel data generated from a random sampling of the Spanish-German corpora
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+ available on [Opus](https://opus.nlpl.eu/) and translated into Catalan using the [PlanTL es-ca](https://huggingface.co/PlanTL-GOB-ES/mt-plantl-es-ca) model. -->
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+
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+ The corpus is a combination of the following original datasets collected from [Opus](https://opus.nlpl.eu/):
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+ MultiCCAligned, WikiMatrix, GNOME, KDE4, OpenSubtitles, GlobalVoices, Tatoeba.
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+
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+ All data was filtered according to two specific criteria:
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+ - Alignment: sentence level alignments were calculated using [LaBSE](https://huggingface.co/sentence-transformers/LaBSE) and sentence pairs with a score below 0.75 were discarded.
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+
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+ - Language identification: the probability of being the target language was calculated using [Lingua.py](https://github.com/pemistahl/lingua-py) and sentences with a language probability score below 0.5 were discarded.
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+ The filtered datasets are then concatenated and deduplicated to form the final corpus.
 
 
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  #### Who are the source language producers?
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  [Opus](https://opus.nlpl.eu/)
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+ <!-- [SoftCatalà](https://github.com/Softcatala/Europarl-catalan) -->
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  ### Annotations
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