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Propicto

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propicto-orfeo-simple/README.md ADDED
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+ # Propicto-Orféo-Simple
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+
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+ ### Dataset description:
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+
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+ __Propicto-Orféo-Simple__ is a small-scale dataset extracted from the French __Orféo-CEFC__ (*Corpus d'Étude pour le Français Contemporain*) corpus, in which triplets of speech-transcriptions pairs are aligned to sentence-level expert simplifications in French.
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+
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+ This work is part of the __PROPICTO__ (French acronym standing for *PRojection du langage Oral vers des unités PICTOgraphiques*) project, funded by the Swiss National Science Foundation (N°197864) and the French National Research Agency (ANR-20-CE93-0005). This research program is conducted by the Department of Translation Technology (TIM) at University of Geneva and the Study Group for Machine Translation and Automated Processing of Languages and Speech (GETALP), attached to the Grenoble Informatics Laboratory (LIG). Further information can be found on __[Ormaechea et al, 2023]__.
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+
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+ __Propicto-Orféo-Simple__ was created to provide a corpus for the evaluation of automatic spontaneous speech simplification systems. In the absence of guidelines to direct this process, we adopted an intuitive simplification approach, so as to investigate the crafted simplifications based on expert linguists' criteria.
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+
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+ To ensure the reliability and knowledge extrapolation from the data sample, we perfomed stratified sampling on __Orféo-CEFC__, by which we obtained a set of 100 segments. The sampling was proportionate, and contained segments from the 12 subcorpora comprised within this corpus. The subcorpora cover a wide range of communicative situations (i.e., interviews, tales, phone calls, etc.), environments (friendly, academic or familiar) and degrees of spontaneity, ranging from professional situations to everyday life ones. More precisely, we relied on the Orféo-CEFC partitioning created by __[Pupier et al, 2022]__ and use their evaluation set as the population for our study, which amounts to 21,459 segments.
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+
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+ __Keywords:__
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+ - spontaneous speech,
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+ - simplification,
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+ - expert annotation,
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+ - French language.
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+
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+ ### Files:
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+
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+ __Propicto-Orféo-Simple__ is a small-scale dataset that maps the already existing audio files and transcripts of Orféo-CEFC with simplified equivalents crafted by human experts:
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+
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+ - Audio clips are stored in the folder: __propicto_orfeo_simple_clips/__. They are in .wav format with a sample rate of 16kHz.
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+ - The file __propicto_orfeo_simple_pairs.json__ contains the aligned clips-transcripts-simplifications triplets. It is structured as follows:
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+ 1. __id_utterance__: the segment id, which points to the corresponding audio clip.
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+ 2. __subcorpus__: name of the subcorpus to which the segment belongs.
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+ 2. __utterance__: the original transcript associated to the audio clip.
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+ 3. __expert_1_simplification__: simplification proposed by the first expert linguist.
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+ 4. __expert_2_simplification__: simplification proposed by the second expert linguist.
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+
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+
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+ ### References:
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+
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+ - __[Ormaechea et al, 2023]__ L. Ormaechea, P. Bouillon, M. Coavoux, E. Esperança-Rodier, J. Gerlach, J. Goulian, B. Lecouteux, C. Macaire, J. Mutal, M. Norré, A. Pupier, D. Schwab. 2023. PROPICTO: Developing Speech-to-Pictograph Translation Systems to Enhance Communication Accessibility. In Proc. of the 24th Annual Conference of the European Association for Machine Translation, 515–516.
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+ - __[Pupier et al, 2022]__ A. Pupier, M. Coavoux, B. Lecouteux, J. Goulian. 2022. End-to-End Dependency Parsing of Spoken French. Proc. Interspeech 2022, 1816-1820.
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