{"id":3608,"date":"2023-08-03T20:16:05","date_gmt":"2023-08-03T20:16:05","guid":{"rendered":"https:\/\/dailyai.com\/?p=3608"},"modified":"2023-08-03T20:24:13","modified_gmt":"2023-08-03T20:24:13","slug":"ai-generated-deep-fake-voices-trick-over-1-4-of-participants-in-a-new-study","status":"publish","type":"post","link":"https:\/\/dailyai.com\/es\/2023\/08\/ai-generated-deep-fake-voices-trick-over-1-4-of-participants-in-a-new-study\/","title":{"rendered":"Voces falsas generadas por inteligencia artificial enga\u00f1an a m\u00e1s de 1\/4 de los participantes en un nuevo estudio"},"content":{"rendered":"

Un nuevo estudio ha descubierto que incluso cuando las personas son conscientes de que podr\u00edan estar escuchando un discurso falso, siguen teniendo dificultades para identificar con fiabilidad las voces falsas.<\/b><\/p>\n

Esto se aplica tanto a hablantes de ingl\u00e9s como de mandar\u00edn, lo que subraya que las voces falsas graves son probablemente eficaces en muchos idiomas.\u00a0<\/span><\/p>\n

Investigadores del University College de Londres pidieron a 500 personas que identificaran voces falsas profundas en varios clips de audio. Algunos de los clips inclu\u00edan una voz femenina aut\u00e9ntica que le\u00eda frases gen\u00e9ricas en ingl\u00e9s o mandar\u00edn, mientras que otros eran falsificaciones profundas producidas por IA generativas entrenadas en voces femeninas.<\/span><\/p>\n

En <\/span>estudiar<\/span><\/a> Los participantes se dividieron en dos grupos, cada uno sometido a una forma distinta del experimento.\u00a0<\/span><\/p>\n

A un grupo se le presentaron 20 muestras de voz en su lengua materna y tuvo que discernir si los clips eran reales o falsos. Los participantes identificaron correctamente las falsificaciones profundas y las voces aut\u00e9nticas aproximadamente el 73% de las veces, tanto para las muestras de voz en ingl\u00e9s como en mandar\u00edn.\u00a0<\/span><\/p>\n

A otro grupo se le proporcionaron 20 pares de clips de audio seleccionados al azar. Cada par conten\u00eda la misma frase pronunciada por un humano y la falsificaci\u00f3n profunda, y los participantes deb\u00edan identificar la falsificaci\u00f3n. Esto aument\u00f3 la precisi\u00f3n de detecci\u00f3n a 85,59%.<\/span><\/p>\n

En el primer experimento, es probable que la detecci\u00f3n humana de falsificaciones profundas en la vida real sea peor de lo que sugieren los resultados, ya que no se advertir\u00eda a la gente de que podr\u00eda estar escuchando habla generada por IA.\u00a0<\/span><\/p>\n

Por el contrario, en el segundo experimento, los oyentes tienen una opci\u00f3n binaria, lo que les otorga una ventaja.<\/span><\/p>\n

Curiosamente, hubo relativamente poca diferencia en los resultados del ingl\u00e9s en mandar\u00edn.\u00a0<\/span><\/p>\n

Aumentan las estafas por discursos falsos en la vida real<\/h2>\n

\"Esta configuraci\u00f3n no es totalmente representativa de la vida real\", afirma Mai. \"Los oyentes no sabr\u00edan de antemano si lo que est\u00e1n escuchando es real, y factores como el sexo y la edad del hablante podr\u00edan afectar a la detecci\u00f3n\".<\/span><\/p>\n

Sin embargo, existen otras limitaciones, ya que el estudio no desafi\u00f3 a los oyentes a determinar falsificaciones profundas dise\u00f1adas para sonar como alguien que conocen, como un hijo, una madre, etc. Si los estafadores se dirigieran a alguien con una falsificaci\u00f3n profunda, es casi seguro que clonar\u00edan la voz de alguien. Esto es relativamente f\u00e1cil si alguien ha subido audio o v\u00eddeos de s\u00ed mismo a Internet, por ejemplo, para un v\u00eddeo en las redes sociales, un podcast, una emisi\u00f3n de radio o televisi\u00f3n.\u00a0<\/span><\/p>\n

Esto ya est\u00e1 ocurriendo, con una <\/span>Encuesta de McAfee<\/span><\/a> que muestra que aproximadamente 1 de cada 4 adultos es consciente de que se est\u00e1n produciendo fraudes de voz falsa. <\/span><\/p>\n

El fraude relacionado con la <\/span>aumento en China<\/span><\/a>y un analista <\/span>predijo que<\/span><\/a> El fraude apoyado en la IA podr\u00eda costar caro a las personas y a las econom\u00edas. Hay numerosas an\u00e9cdotas aterradoras de personas que ya han sido blanco de llamadas falsas, a menudo en forma de un familiar asustado que pide dinero para salir de una situaci\u00f3n dif\u00edcil.\u00a0<\/span><\/p>\n

Este estudio descubri\u00f3 que las voces falsas \"se mueven por el valle inquietante\", imitando el sonido natural de las voces humanas pero careciendo de los matices sutiles que provocan sospechas en algunos oyentes. Por supuesto, las voces falsas profundas de la IA no dejan de mejorar.\u00a0<\/span><\/p>\n

En general, el estudio demuestra que la tecnolog\u00eda actual ya es muy competente, y los intentos de mejorar la capacidad de los individuos para detectar voces falsas en el estudio fueron en gran medida infructuosos.\u00a0<\/span><\/p>\n

Los autores subrayan la necesidad de desarrollar detectores de voz AI competentes y de educar a la poblaci\u00f3n sobre lo sofisticadas que son ya las voces falsas profundas. <\/span><\/p>\n

Ser\u00eda muy \u00fatil investigar en el futuro las falsificaciones profundas replicando las voces de personas conocidas por los participantes en el estudio.<\/span><\/p>\n

Hay formas pr\u00e1cticas de identificar las estafas de discurso falso profundo, como establecer palabras clave entre familiares o pedir a quienes llaman que describan un dato personal conocido por todos.<\/p>","protected":false},"excerpt":{"rendered":"

Un nuevo estudio ha descubierto que incluso cuando las personas son conscientes de que podr\u00edan estar escuchando voces falsas profundas, siguen teniendo dificultades para identificarlas de forma fiable. Esto se aplica tanto a hablantes de ingl\u00e9s como de mandar\u00edn, lo que pone de relieve que las voces falsas profundas son probablemente eficaces en muchos idiomas. Investigadores del University College de Londres pidieron a 500 personas que identificaran voces falsas profundas en varios clips de audio. Algunos de ellos inclu\u00edan una voz femenina aut\u00e9ntica que le\u00eda frases gen\u00e9ricas en ingl\u00e9s o mandar\u00edn, mientras que otros eran falsificaciones profundas producidas por IA generativas entrenadas en voces femeninas. Los participantes en el estudio se dividieron en dos grupos.<\/p>","protected":false},"author":2,"featured_media":3610,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[88],"tags":[162,161,273],"class_list":["post-3608","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ethics","tag-deep-fake","tag-fraud","tag-speech"],"yoast_head":"\nAI-generated deep fake voices trick over 1\/4 of participants in a new study | DailyAI<\/title>\n<meta name=\"description\" content=\"A new study found that even when people are aware they could be listening to deep fake speech, they still struggle to reliably identify fake voices.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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