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You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made.
The charts below show the way in which the International Phonetic Alphabet (IPA) represents French language pronunciations in Wikipedia articles. For a guide to adding IPA characters to Wikipedia articles, see Template:IPA and Wikipedia:Manual of Style/Pronunciation § Entering IPA characters.
Such phenomena are conditioned lexically and regionally. For example, for the word difficile 'difficult', the standard pronunciation [d͡zifisɪl] is found throughout Quebec, but the alternative pronunciations [d͡zifɪsɪl], [d͡zɪfɪsɪl] and [d͡zɪfsɪl] are also used. The phonemes /a/ and /ɑ/ are distinct.
French orthography encompasses the spelling and punctuation of the French language.It is based on a combination of phonemic and historical principles. The spelling of words is largely based on the pronunciation of Old French c. 1100 –1200 AD, and has stayed more or less the same since then, despite enormous changes to the pronunciation of the language in the intervening years.
French phonology is the sound system of French.This article discusses mainly the phonology of all the varieties of Standard French.Notable phonological features include the uvular r present in some accents, nasal vowels, and three processes affecting word-final sounds:
Liaison only happens when the following word starts with a vowel or semivowel, and is restricted to word sequences whose components are linked in sense, e.g., article + noun, adjective + noun, personal pronoun + verb, and so forth. This indicates that liaison is primarily active in high-frequency word associations (collocations).
An electronic repository (and bibliography) of articles, books and papers in the field of machine translation and computer-based translation technology; Machine translation (computer-based translation) – Publications by John Hutchins (includes PDFs of several books on machine translation)
Generative language models are not trained on the translation task, let alone on a parallel dataset. Instead, they are trained on a language modeling objective, such as predicting the next word in a sequence drawn from a large dataset of text. This dataset can contain documents in many languages, but is in practice dominated by English text. [36]