{"id":35276,"date":"2025-01-16T07:16:49","date_gmt":"2025-01-16T06:16:49","guid":{"rendered":"https:\/\/www.markt-kom.com\/?p=229010"},"modified":"2025-01-16T07:42:36","modified_gmt":"2025-01-16T06:42:36","slug":"automatische-spracherkennung-macht-grosse-fortschritte","status":"publish","type":"post","link":"https:\/\/www.organisator.ch\/fr\/marketing\/2025-01-16\/automatische-spracherkennung-macht-grosse-fortschritte\/","title":{"rendered":"La reconnaissance vocale automatique fait de grands progr\u00e8s"},"content":{"rendered":"
\"\"<\/a>\r\n
Dans un environnement bruyant, les syst\u00e8mes modernes de reconnaissance vocale atteignent une pr\u00e9cision impressionnante. (Image symbolique : Unsplash.com)<\/figcaption>\r\n<\/figure>\r\n

Dans une \u00e9tude r\u00e9cente, Eleanor Chodroff, linguiste informatique de l'UZH, a examin\u00e9 avec Chloe Patman de l'Universit\u00e9 de Cambridge la capacit\u00e9 des syst\u00e8mes ASR modernes \u00e0 faire face \u00e0 des conditions d'\u00e9coute difficiles. Les syst\u00e8mes \"wav2vec 2.0\" de Meta et \"Whisper large-v3\" d'OpenAI ont \u00e9t\u00e9 test\u00e9s. Le crit\u00e8re : la performance des locuteurs natifs britanniques.<\/p>\r\n

Les tests se sont d\u00e9roul\u00e9s dans des conditions extr\u00eames, allant d'un bruit semblable \u00e0 celui de la voix \u00e0 un bruit r\u00e9aliste de pub, avec ou sans masque facial en coton. R\u00e9sultat : les humains ont globalement montr\u00e9 les meilleures performances, mais le syst\u00e8me OpenAI \"Whisper large-v3\" les a surpass\u00e9s dans presque tous les sc\u00e9narios. Ce n'est que dans le bruit des bars qu'il \u00e9tait \u00e0 la hauteur de l'audition humaine.<\/p>\r\n

La capacit\u00e9 de \"Whisper large-v3\" \u00e0 traiter correctement la parole, m\u00eame sans soutien contextuel, a \u00e9t\u00e9 particuli\u00e8rement frappante.<\/p>\r\n

La diff\u00e9rence d\u00e9cisive<\/strong><\/h3>\r\n

L'\u00e9norme performance de \"Whisper\" repose sur des quantit\u00e9s gigantesques de donn\u00e9es d'entra\u00eenement. Alors que \"wav2vec 2.0\" de Meta a \u00e9t\u00e9 entra\u00een\u00e9 avec 960 heures de donn\u00e9es vocales, OpenAI a eu recours \u00e0 plus de 75 ans de donn\u00e9es vocales pour son syst\u00e8me standard. Le mod\u00e8le le plus performant a m\u00eame utilis\u00e9 plus de 500 ans de donn\u00e9es vocales. En comparaison, l'\u00eatre humain d\u00e9veloppe des capacit\u00e9s similaires en quelques ann\u00e9es seulement - un aspect remarquable, comme le souligne l'auteur principal de l'\u00e9tude, Eleanor Chodroff. \"En outre, la reconnaissance automatique de la parole dans presque toutes les autres langues reste un grand d\u00e9fi\".<\/p>\r\n

Diff\u00e9rentes sources d'erreurs<\/strong><\/h3>\r\n

L'\u00e9tude a \u00e9galement montr\u00e9 que les hommes et les machines \u00e9chouent de diff\u00e9rentes mani\u00e8res. Les humains cr\u00e9ent presque toujours des phrases grammaticalement correctes, mais \u00e9crivent souvent des fragments de phrases. En revanche, \"wav2vec 2.0\" g\u00e9n\u00e9rait souvent un charabia incompr\u00e9hensible dans des conditions difficiles. \"Whisper\" pouvait produire des phrases grammaticalement correctes, mais remplissait les lacunes de contenu avec des informations totalement erron\u00e9es.\u00a0(pd\/swi)<\/em><\/p>\r\n

\r\n

Le site \u00c9tude \"Speech recognition in adverse conditions by humans and machines\" par Chloe Patman et Eleanor Chodroff<\/a> peut \u00eatre consult\u00e9 en d\u00e9tail ici. <\/em><\/p>","protected":false},"excerpt":{"rendered":"

Les hommes ou les machines peuvent-ils mieux reconna\u00eetre la parole ? Dans des environnements bruyants tels que le bruit des bars, les syst\u00e8mes modernes de reconnaissance vocale (ASR) atteignent une pr\u00e9cision impressionnante - et surpassent m\u00eame les humains dans certains sc\u00e9narios. Mais c'est pr\u00e9cis\u00e9ment ce qui montre \u00e0 quel point la performance humaine est en r\u00e9alit\u00e9 remarquable.<\/p>","protected":false},"author":8,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_yoast_wpseo_focuskw":"Spracherkennung","_yoast_wpseo_metadesc":"Mensch oder Maschine: Wer erkennt Sprache besser? 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