{"id":100668,"date":"2021-07-02T16:22:45","date_gmt":"2021-07-02T14:22:45","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/kompaniya-google-otkryla-nedostayushhie-ishodnye-teksty-dlya-audiokodeka-lyra"},"modified":"2021-07-02T16:22:45","modified_gmt":"2021-07-02T14:22:45","slug":"kompaniya-google-otkryla-nedostayushhie-ishodnye-teksty-dlya-audiokodeka-lyra","status":"publish","type":"post","link":"https:\/\/prohoster.info\/fr\/blog\/news\/kompaniya-google-otkryla-nedostayushhie-ishodnye-teksty-dlya-audiokodeka-lyra","title":{"rendered":"La soci\u00e9t\u00e9 Google a rendu publics les codes sources manquants pour le codec audio Lyra","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

La soci\u00e9t\u00e9 Google a publi\u00e9 une mise \u00e0 jour du codec audio Lyra 0.0.2, optimis\u00e9 pour atteindre une qualit\u00e9 maximale de transmission vocale sur des canaux de communication tr\u00e8s lents. Le codec a \u00e9t\u00e9 ouvert d\u00e9but avril, mais \u00e9tait fourni avec une biblioth\u00e8que math\u00e9matique propri\u00e9taire. Dans la version 0.0.2, ce probl\u00e8me a \u00e9t\u00e9 r\u00e9solu et un remplacement ouvert a \u00e9t\u00e9 cr\u00e9\u00e9 pour ladite biblioth\u00e8que \u2014 sparse_matmul, qui, comme le codec lui-m\u00eame, est distribu\u00e9 sous la licence Apache 2.0. Parmi les autres am\u00e9liorations, on peut noter la possibilit\u00e9 d'utiliser le syst\u00e8me de construction Bazel avec le compilateur GCC, et l'utilisation de cette combinaison par d\u00e9faut sous Linux au lieu de Bazel+Clang. <\/p>\n

Rappelons que, en termes de qualit\u00e9 des donn\u00e9es vocales transmises \u00e0 basse vitesse, Lyra surpasse consid\u00e9rablement les codecs traditionnels qui utilisent des m\u00e9thodes de traitement num\u00e9rique des signaux. Pour atteindre une qualit\u00e9 \u00e9lev\u00e9e de transmission vocale dans des conditions de capacit\u00e9 de transmission d'information limit\u00e9e, en plus des m\u00e9thodes habituelles de compression sonore et de transformation des signaux, Lyra utilise un mod\u00e8le de voix bas\u00e9 sur un syst\u00e8me d'apprentissage automatique, permettant de recr\u00e9er les informations manquantes sur la base des caract\u00e9ristiques typiques de la parole. Le mod\u00e8le utilis\u00e9 pour g\u00e9n\u00e9rer le son a \u00e9t\u00e9 entra\u00een\u00e9 sur plusieurs milliers d'heures d'enregistrements de voix dans plus de 70 langues. Les performances de la mise en \u0153uvre propos\u00e9e sont suffisantes pour coder et d\u00e9coder la voix en temps r\u00e9el sur des smartphones de milieu de gamme, avec un d\u00e9lai de transmission du signal d'environ 90 millisecondes.
\n
Source : opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

\u041a\u043e\u043c\u043f\u0430\u043d\u0438\u044f Google \u043e\u043f\u0443\u0431\u043b\u0438\u043a\u043e\u0432\u0430\u043b\u0430 \u043e\u0431\u043d\u043e\u0432\u043b\u0435\u043d\u0438\u0435 \u0430\u0443\u0434\u0438\u043e\u043a\u043e\u0434\u0435\u043a\u0430 Lyra 0.0.2, \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u043e\u0433\u043e \u0434\u043b\u044f \u0434\u043e\u0441\u0442\u0438\u0436\u0435\u043d\u0438\u044f \u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u043e\u0433\u043e \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430 \u043f\u0435\u0440\u0435\u0434\u0430\u0447\u0438 \u0440\u0435\u0447\u0438 \u043f\u0440\u0438 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0438 \u043e\u0447\u0435\u043d\u044c \u043c\u0435\u0434\u043b\u0435\u043d\u043d\u044b\u0445 \u043a\u0430\u043d\u0430\u043b\u043e\u0432 \u0441\u0432\u044f\u0437\u0438. \u041a\u043e\u0434\u0435\u043a \u0431\u044b\u043b \u043e\u0442\u043a\u0440\u044b\u0442 \u0432 \u043d\u0430\u0447\u0430\u043b\u0435 \u0430\u043f\u0440\u0435\u043b\u044f, \u043d\u043e \u043f\u043e\u0441\u0442\u0430\u0432\u043b\u044f\u043b\u0441\u044f \u0432 \u043f\u0440\u0438\u0432\u044f\u0437\u043a\u0435 \u043a \u043f\u0440\u043e\u043f\u0440\u0438\u0435\u0442\u0430\u0440\u043d\u043e\u0439 \u043c\u0430\u0442\u0435\u043c\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0439 \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0435. \u0412 \u0432\u0435\u0440\u0441\u0438\u0438 0.0.2 \u0434\u0430\u043d\u043d\u044b\u0439 \u043d\u0435\u0434\u043e\u0441\u0442\u0430\u0442\u043e\u043a \u0443\u0441\u0442\u0440\u0430\u043d\u0451\u043d \u0438 \u0434\u043b\u044f \u0443\u043a\u0430\u0437\u0430\u043d\u043d\u043e\u0439 \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0438 \u0441\u043e\u0437\u0434\u0430\u043d\u0430 \u043e\u0442\u043a\u0440\u044b\u0442\u0430\u044f \u0437\u0430\u043c\u0435\u043d\u0430 — sparse_matmul, \u043a\u043e\u0442\u043e\u0440\u0430\u044f \u043a\u0430\u043a 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