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chore: fiddling around some more chore: add ctranslate2 and timestamped chore: add performance markers chore: refactor test chore: change worflow name chore: ensure Python3 chore(duration): convert to chai/mocha syntahx chore(transcription): add individual tests for others transcribers chore(transcription): implement formats test of all implementations Also compare result of other implementation to the reference implementation chore(transcription): add more test case with other language and models size and local model chore(test): wip ctranslate 2 adapat chore(transcription): wip transcript file and benchmark chore(test): clean a bit chore(test): clean a bit chore(test): refacto timestamed spec chore(test): update workflow chore(test): fix glob expansion with sh chore(test): extract some hw info chore(test): fix async tests chore(benchmark): add model info feat(transcription): allow use of a local mode in timestamped-whisper feat(transcription): extract run and profiling info in own value object feat(transcription): extract run concept in own class an run more bench chore(transcription): somplify run object only a uuid is now needed and add more benchmark scenario docs(transcription): creates own package readme docs(transcription): add local model usage docs(transcription): update README fix(transcription): use fr video for better comparison chore(transcription): make openai comparison passed docs(timestamped): clea chore(transcription): change transcribers transcribe method signature Introduce whisper builtin model. fix(transcription): activate language detection Forbid transcript creation without a language. Add `languageDetection` flag to an engine and some assertions. Fix an issue in `whisper-ctranslate2` : https://github.com/Softcatala/whisper-ctranslate2/pull/93 chore(transcription): use PeerTube time helpers instead of custom ones Update existing time function to output an integer number of seconds and add a ms human-readable time formatter with hints of tests. chore(transcription): use PeerTube UUID helpers chore(transcription): enable CER evaluation Thanks to this recent fix in Jiwer <3 https://github.com/jitsi/jiwer/issues/873 chore(jiwer): creates JiWer package I'm not very happy with the TranscriptFileEvaluator constructor... suggestions ? chore(JiWer): add usage in README docs(jiwer): update JiWer readme chore(transcription): use FunMOOC video in fixtures chore(transcription): add proper english video fixture chore(transcription): use os tmp directory where relevant chore(transcription): fix jiwer cli test reference.txt chore(transcription): move benchmark out of tests chore(transcription): remove transcription workflow docs(transcription): add benchmark info fix(transcription): use ms precision in other transcribers chore(transcription): simplify most of the tests chore(transcription): remove slashes when building path with join chore(transcription): make fromPath method async chore(transcription): assert path to model is a directory for CTranslate2 transcriber chore(transcription): ctranslate2 assertion chore(transcription): ctranslate2 assertion chore(transcription): add preinstall script for Python dependencies chore(transcription): add download and unzip utils functions chore(transcription): add download and unzip utils functions chore(transcription): download & unzip models fixtures chore(transcription): zip chore(transcription): raise download file test timeout chore(transcription): simplify download file test chore(transcription): add transcriptions test to CI chore(transcription): raise test preconditions timeout chore(transcription): run preinstall scripts before running ci chore(transcription): create dedicated tmp folder for transcriber tests chore(transcription): raise timeout some more chore(transcription): raise timeout some more chore(transcription): raise timeout some more chore(transcription): raise timeout some more chore(transcription): raise timeout some more chore(transcription): raise timeout some more chore(transcription): raise timeout some more chore(transcription): raise timeout some more chore(transcription): use short video for local model test chore(transcription): raise timeout some more chore(transcription): raise timeout some more chore(transcription): raise timeout some more chore(transcription): setup verbosity based on NODE_ENV value
10 lines
1.4 KiB
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10 lines
1.4 KiB
Text
Communiquer lors d'une classe transplantée. Utiliser les photos prises lors de cette classe pour raconter quotidiennement le séjour vécu.
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C'est le scénario pédagogique présenté par Monsieur Navoli, professeur en cycle 3 sur une école élémentaire de Montpellier.
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La première application utilisée sera la médiathèque. L'enseignant va alors transférer les différentes photos réalisées lors de la classe transplantée.
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Dans un dossier spécifique pour que les élèves puissent le retrouver plus facilement. Il téléverse donc ses photos dans le dossier, dans l'ENT, dans la médiathèque de la classe.
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Pour terminer, il s'assure que le dossier soit bien ouvert aux utilisateurs afin que tout le monde puisse l'utiliser.
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Les élèves par la suite utiliseront le blog, à partir de leurs notes, il pourront, seul ou à 2 par poste rédiger un article dans leur ENT.
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Ils illustreront ces articles à l'aide des photos et documents numériques mis en accès libre dans l'ENT.
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Pour ce faire, il pourront utiliser l'éditeur avancé qui les renverra directement dans la médiathèque de la classe, où ils pourront retrouver le dossier créé par leur enseignant.
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Une fois leur article terminé, les élèves soumettront celui-ci au professeur qui pourra soit l'annoter pour correction ou le publier.
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Ensuite, il pourront lire et commenter ceux de leurs camarades, ou répondre aux commentaires de la veille.
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