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99. The Technical Side of Deep Fakes

 
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When? This feed was archived on December 12, 2020 08:26 (4+ y ago). Last successful fetch was on March 02, 2025 02:12 (5M ago)

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Manage episode 294560472 series 2501898
תוכן מסופק על ידי Salesforce Engineering. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי Salesforce Engineering או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.

Julián Duque is a Lead Developer Advocate at Salesforce and Heroku, and he's continuing a previous discussion with some members of Respeecher. Respeecher has created AI software which works within the speech-to-speech domain: it takes one voice and makes it sound exactly like another. Dmytro Bielievtsov, its CTO and co-founder, explains the practical uses of the software, such as re=recording the lines of an actor who is unavailable, or bringing historical figures to life in a museum.

In terms of sophistication, there are quite a few speech ML models already available on the Internet. The best source of audio to duplicate the speech patterns of a famous person is to grab an audiobook and pass it through one of these pre-existing models. But these models produce outputs which are poor in quality. That's one reason that speech-to-speech is hard to fake. The variation in our mouths and speech patterns, not to mention the emotive qualities, make the process of creating duplicate voices extremely difficult to pull off. One way Respeecher data can't be faked is by the fact that they position themselves as a B2B business, dealing with studios and other large estates which have access to immense amounts of hard-to-acquire sound data. The likelihood of another entity abusing a well-known voice is close to none. Another feature is that the audio is watermarked. Certain "artifacts" are embedded into the audio, which are imperceptible to humans, but easily identifiable by a computer program.

There's a consortium of several companies working on synthesized media who strategize in Slack on various ways to keep the tech from being misused. As well, Dmytro believes that there needs to more investment in education, to let people know that such technology exists, and to therefore be a bit suspicious with media they encounter online.

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132 פרקים

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99. The Technical Side of Deep Fakes

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iconשתפו
 

סדרה בארכיון ("עדכון לא פעיל" status)

When? This feed was archived on December 12, 2020 08:26 (4+ y ago). Last successful fetch was on March 02, 2025 02:12 (5M ago)

Why? עדכון לא פעיל status. השרתים שלנו לא הצליחו לאחזר פודקאסט חוקי לזמן ממושך.

What now? You might be able to find a more up-to-date version using the search function. This series will no longer be checked for updates. If you believe this to be in error, please check if the publisher's feed link below is valid and contact support to request the feed be restored or if you have any other concerns about this.

Manage episode 294560472 series 2501898
תוכן מסופק על ידי Salesforce Engineering. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי Salesforce Engineering או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.

Julián Duque is a Lead Developer Advocate at Salesforce and Heroku, and he's continuing a previous discussion with some members of Respeecher. Respeecher has created AI software which works within the speech-to-speech domain: it takes one voice and makes it sound exactly like another. Dmytro Bielievtsov, its CTO and co-founder, explains the practical uses of the software, such as re=recording the lines of an actor who is unavailable, or bringing historical figures to life in a museum.

In terms of sophistication, there are quite a few speech ML models already available on the Internet. The best source of audio to duplicate the speech patterns of a famous person is to grab an audiobook and pass it through one of these pre-existing models. But these models produce outputs which are poor in quality. That's one reason that speech-to-speech is hard to fake. The variation in our mouths and speech patterns, not to mention the emotive qualities, make the process of creating duplicate voices extremely difficult to pull off. One way Respeecher data can't be faked is by the fact that they position themselves as a B2B business, dealing with studios and other large estates which have access to immense amounts of hard-to-acquire sound data. The likelihood of another entity abusing a well-known voice is close to none. Another feature is that the audio is watermarked. Certain "artifacts" are embedded into the audio, which are imperceptible to humans, but easily identifiable by a computer program.

There's a consortium of several companies working on synthesized media who strategize in Slack on various ways to keep the tech from being misused. As well, Dmytro believes that there needs to more investment in education, to let people know that such technology exists, and to therefore be a bit suspicious with media they encounter online.

Links from this episode

  continue reading

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