These Deepfake Sounds Will Help Trans Gamers


Fred, a trans man, clicked his mouse, and his tone of voice suddenly sank. He moved the voice change algorithms gives that like a quick vocal cord shift. “It’s a‘ Seth, ’” he said, to a person he tried on a Zoom call with a reporter. Afterwards, he moved to speak as “Joe,” in whose voice was more nasal and loud.

Fred’s friend Jane, a trans woman who was also trying out prototype software, laughed and showed off some artificial sounds she wanted for their feminine sound. “This one is‘ Courtney ’” – bright and sharp. “Here’s‘ Maya ’” – higher tone, sometimes too much. “It’s‘ Alicia, ’the one I found to have the most difference in voice, ”he concluded slowly. The glitches are big enough to ease the passing thought that the pair may not have joined the call in their “real” voices to begin with.

Fred and Jane were early testers of technology from the start Modulate that could add new pleasures, protections, and complications to online communication. WIRED does not use their real names to protect their privacy; Trans people are often the target of online harassment. Software is the latest example of deceptive potential artificial intelligence technology that is able to mix what really looks like video or audio, sometimes called a term deepfakes.

Modulate owners Mike Pappas and Carter Huffman initially thought the technology they called “skin skins” could make gaming more fun by allowing players to voice the characters. As the pair set up studios and recruited early testers, they also heard a choral interest in using voice skins as a safeguard of privacy. More than 100 people asked if technology could alleviate the disphoria caused by the misunderstanding between their voice recognition and gender.

“We know a lot of people don’t feel like they can participate in online communities because their voice puts them at greater risk,” Pappas, CEO of Modulate, said. The company is now working with game companies to provide voice skins in ways that offer both fun and privacy options, while also promising to prevent them from becoming tools of deception or harassment themselves.

Games like Fortnite and social apps like Discord that have become more common to engage in voice chats with strangers on the internet. Like the early days of texting via the internet, voice advancement unlocks both new joys and fears.

The Anti-Defamation League found last year that nearly half of players experienced harassment via voice chat while playing, more so through text. A sexist streak in gaming culture causes women and LGBTQ people to be selected for special abuse. When Riot Games launched the team -based shooter Giving value in 2020, executive director Anna Donlon said she was shocked to see a culture of sexist harassment growing so rapidly. “I don’t use voice chat if I’m the only one to go,” he said said WIRED.

Modulate’s technology isn’t yet widely available, but Pappas said he’s talked to game companies interested in implementing it. One possible approach is to create indoor modes in a game or community where everyone is given a skin tone corresponding to their character, whether a gruff troll or knight in armor; on the other hand, voices can be pointed at random.

on June two of Modulate’s voice launched inside a preview of an app called Animaze, which transforms a user into a digital avatar in livestreams or video calls. The developer, Holotech Studios, markets sounds as part of privacy and a way to “morph your voice to better fit a character with a different age, gender, or body type than yours. . ” Modulate also provides software to game companies that automatically notifies moderators of signs of abuse in voice chats.

Modulate’s voice skins are activated by machine learning Algorithms that adjust the audio standards of a person’s voice so that it is similar to others. To teach its technology to speak in many different tones and timbres, the company collected and analyzed audio from hundreds of artists reading scripts created to deliver a different tone and feel. Individual sound skins are created by tuning algorithms to copy the sound of a specific voice artist.



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