La compa\u00f1\u00eda Google ha publicado la actualizaci\u00f3n del c\u00f3dec de audio Lyra 0.0.2, optimizado para lograr la mejor calidad de transmisi\u00f3n de voz utilizando canales de comunicaci\u00f3n muy lentos. El c\u00f3dec se abri\u00f3 a principios de abril, pero se entreg\u00f3 vinculado a una biblioteca matem\u00e1tica propietaria. En la versi\u00f3n 0.0.2, este inconveniente ha sido corregido y se ha creado un reemplazo abierto para la biblioteca mencionada \u2014 sparse_matmul, que al igual que el propio c\u00f3dec se distribuye bajo la licencia Apache 2.0. Entre otras mejoras, se destaca la posibilidad de utilizar el sistema de construcci\u00f3n Bazel con el compilador GCC y el uso de esta combinaci\u00f3n por defecto en Linux en lugar de Bazel+Clang. <\/p>\n
Cabe recordar que en t\u00e9rminos de calidad de los datos de voz transmitidos a bajas velocidades, Lyra supera significativamente a los c\u00f3decs tradicionales que utilizan m\u00e9todos de procesamiento de se\u00f1ales digitales. Para lograr una alta calidad en la transmisi\u00f3n de voz en condiciones de un volumen limitado de informaci\u00f3n transmitida, adem\u00e1s de los m\u00e9todos de compresi\u00f3n de sonido y conversi\u00f3n de se\u00f1ales habituales, Lyra utiliza un modelo de lenguaje basado en un sistema de aprendizaje autom\u00e1tico que permite recrear la informaci\u00f3n que falta bas\u00e1ndose en caracter\u00edsticas t\u00edpicas de la voz. El modelo utilizado para la generaci\u00f3n de sonido ha sido entrenado con miles de horas de grabaciones de voces en m\u00e1s de 70 idiomas. La eficiencia de la implementaci\u00f3n propuesta es suficiente para codificar y decodificar voz en tiempo real en smartphones de gama media, con un retraso de transmisi\u00f3n de se\u00f1al de alrededor de 90 milisegundos. \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 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Fuente: opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"