The company blog post drips with the enthusiasm of a ’90s US infomercial. WellSaid Labs describes what clients can expect from its “eight new digital voice actors!” Tobin is “energetic and insightful.” Paige is “poised and expressive.” Ava is “polished, self-assured, and professional.”
Each one is based on a real voice actor, whose likeness (with consent) has been preserved using AI. Companies can now license these voices to say whatever they need. They simply feed some text into the voice engine, and out will spool a crisp audio clip of a natural-sounding performance.
WellSaid Labs, a Seattle-based startup that spun out of the research nonprofit Allen Institute of Artificial Intelligence, is the latest firm offering AI voices to clients. For now, it specializes in voices for corporate e-learning videos. Other startups make voices for digital assistants, call center operators, and even video-game characters.
Not too long ago, such deepfake voices had something of a lousy reputation for their use in scam calls and internet trickery. But their improving quality has since piqued the interest of a growing number of companies. Recent breakthroughs in deep learning have made it possible to replicate many of the subtleties of human speech. These voices pause and breathe in all the right places. They can change their style or emotion. You can spot the trick if they speak for too long, but in short audio clips, some have become indistinguishable from humans.
AI voices are also cheap, scalable, and easy to work with. Unlike a recording of a human voice actor, synthetic voices can also update their script in real time, opening up new opportunities to personalize advertising.
But the rise of hyperrealistic fake voices isn’t consequence-free. Human voice actors, in particular, have been left to wonder what this means for their livelihoods.
How to fake a voice
Synthetic voices have been around for a while. But the old ones, including the voices of the original Siri and Alexa, simply glued together words and sounds to achieve a clunky, robotic effect. Getting them to sound any more natural was a laborious manual task.
Deep learning changed that. Voice developers no longer needed to dictate the exact pacing, pronunciation, or intonation of the generated speech. Instead, they could feed a few hours of audio into an algorithm and have the algorithm learn those patterns on its own.
“If I’m Pizza Hut, I certainly can’t sound like Domino’s, and I certainly can’t sound like Papa John’s.”
Rupal Patel, founder and CEO of VocaliD
Over the years, researchers have used this basic idea to build voice engines that are more and more sophisticated. The one WellSaid Labs constructed, for example, uses two primary deep-learning models. The first predicts, from a passage of text, the broad strokes of what a speaker will sound like—including accent, pitch, and timbre. The second fills in the details, including breaths and the way the voice resonates in its environment.
Making a convincing synthetic voice takes more than just pressing a button, however. Part of what makes a human voice so human is its inconsistency, expressiveness, and ability to deliver the same lines in completely different styles, depending on the context.
Capturing these nuances involves finding the right voice actors to supply the appropriate training data and fine-tune the deep-learning models. WellSaid says the process requires at least an hour or two of audio and a few weeks of labor to develop a realistic-sounding synthetic replica.
AI voices have grown particularly popular among brands looking to maintain a consistent sound in millions of interactions with customers. With the ubiquity of smart speakers today, and the rise of automated customer service agents as well as digital assistants embedded in cars and smart devices, brands may need to produce upwards of a hundred hours of audio a month. But they also no longer want to use the generic voices offered by traditional text-to-speech technology—a trend that accelerated during the pandemic as more and more customers skipped in-store interactions to engage with companies virtually.
“If I’m Pizza Hut, I certainly can’t sound like Domino’s, and I certainly can’t sound like Papa John’s,” says Rupal Patel, a professor at Northeastern University and the founder and CEO of VocaliD, which promises to build custom voices that match a company’s brand identity. “These brands have thought about their colors. They’ve thought about their fonts. Now they’ve got to start thinking about the way their voice sounds as well.”
Whereas companies used to have to hire different voice actors for different markets—the Northeast versus Southern US, or France versus Mexico—some voice AI firms can manipulate the accent or switch the language of a single voice in different ways. This opens up the possibility of adapting ads on streaming platforms depending on who is listening, changing not just the characteristics of the voice but also the words being spoken. A beer ad could tell a listener to stop by a different pub depending on whether it’s playing in New York or Toronto, for example. Resemble.ai, which designs voices for ads and smart assistants, says it’s already working with clients to launch such personalized audio ads on Spotify and Pandora.
The gaming and entertainment industries are also seeing the benefits. Sonantic, a firm that specializes in emotive voices that can laugh and cry or whisper and shout, works with video-game makers and animation studios to supply the voice-overs for their characters. Many of its clients use the synthesized voices only in pre-production and switch to real voice actors for the final production. But Sonantic says a few have started using them throughout the process, perhaps for characters with fewer lines. Resemble.ai and others have also worked with film and TV shows to patch up actors’ performances when words get garbled or mispronounced.
The US Supreme Court just gutted the EPA’s power to regulate emissions
What was the ruling?
The decision states that the EPA’s actions in a 2015 rule, which included caps on emissions from power plants, overstepped the agency’s authority.
“Capping carbon dioxide emissions at a level that will force a nationwide transition away from the use of coal to generate electricity may be a sensible ‘solution to the crisis of the day,’” the decision reads. “But it is not plausible that Congress gave EPA the authority to adopt on its own such a regulatory scheme.”
Only Congress has the power to make “a decision of such magnitude and consequence,” it continues.
This decision is likely to have “broad implications,” says Deborah Sivas, an environmental law professor at Stanford University. The court is not only constraining what the EPA can do on climate policy going forward, she adds; this opinion “seems to be a major blow for agency deference,” meaning that other agencies could face limitations in the future as well.
The ruling, which is the latest in a string of bombshell cases from the court, fell largely along ideological lines. Chief Justice John Roberts authored the majority opinion, and he was joined by his fellow conservatives: Justices Samuel Alito, Amy Coney Barrett, Neil Gorsuch, Brett Kavanaugh, and Clarence Thomas. Justices Stephen Breyer, Elena Kagan, and Sonia Sotomayor dissented.
What is the decision all about?
The main question in the case was how much power the EPA should have to regulate carbon emissions and what it should be allowed to do to accomplish that job. That question was occcasioned by a 2015 EPA rule called the Clean Power Plan.
The Clean Power Plan targeted greenhouse-gas emissions from power plants, requiring each state to make a plan to cut emissions and submit it to the federal government.
Several states and private groups immediately challenged the Clean Power Plan when it was released, calling it an overreach on the part of the agency, and the Supreme Court put it on hold in 2016. After a repeal of the plan during Donald Trump’s presidency and some legal back-and-forth, a Washington, DC, district court ruled in January 2021 that the Clean Power Plan did fall within the EPA’s authority.
How to track your period safely post-Roe
3. After you delete your app, ask the app provider to delete your data. Just because you removed the app from your phone does not mean the company has gotten rid of your records. In fact, California is the only state where they are legally required to delete your data. Still, many companies are willing to delete it upon request. Here’s a helpful guide from the Washington Post that walks you through how you can do this.
Here’s how to safely track your period without an app.
1. Use a spreadsheet. It’s relatively easy to re-create the functions of a period tracker in a spreadsheet by listing out the dates of your past periods and figuring out the average length of time from the first day of one to the first day of the next. You can turn to one of the many templates already available online, like the period tracker created by Aufrichtig and the Menstrual Cycle Calendar and Period Tracker created by Laura Cutler. If you enjoy the science-y aspect of period apps, templates offer the ability to send yourself reminders about upcoming periods, record symptoms, and track blood flow.
2. Use a digital calendar. If spreadsheets make you dizzy and your entire life is on a digital calendar already, try making your period a recurring event, suggests Emory University student Alexa Mohsenzadeh, who made a TikTok video demonstrating the process.
Mohsenzadeh says that she doesn’t miss apps. “I can tailor this to my needs and add notes about how I’m feeling and see if it’s correlated to my period,” she says. “You just have to input it once.”
3. Go analog and use a notebook or paper planner. We’re a technology publication, but the fact is that the safest way to keep your menstrual data from being accessible to others is to take it offline. You can invest in a paper planner or just use a notebook to keep track of your period and how you’re feeling.
If that sounds like too much work, and you’re looking for a simple, no-nonsense template, try the free, printable Menstrual Cycle Diary available from the University of British Columbia’s Centre for Menstrual Cycle and Ovulation Research.
4. If your state is unlikely to ban abortion, you might still be able to safely use a period-tracking app. The crucial thing will be to choose one that has clear privacy settings and has publicly promised not to share user data with authorities. Quintin says Clue is a good option because it’s beholden to EU privacy laws and has gone on the record with its promise not to share information with authorities.
Composable enterprise spurs innovation
Overall, 74% of companies accelerated plans to move to the cloud by more than a year, jettisoning legacy technologies and operating models to embrace data and applications, according to business analysis firm ZK Research.
A key part of that transformation relied on using applications, usually in the cloud, that integrated apps and data with low-code functionality to create more efficient workflows, more quickly than ever. Low-code is a software development approach for building processes and functionality with little or no code, which allows non-software developers to create applications.
Companies that structure daily workflows around these so-called “composable applications”—often called composable enterprises—have a much tighter relationship between technology and business units and can quickly assemble new applications and services at a fraction of the historical cost.
Composable applications provide a way to build on or add to applications in an easy way—think of building blocks: the work has already been done and additional functionality can be added to the foundational ability.
That flexibility is necessary for the variability of the current workplace and economy, says Zeus Kerravala, founder and principal analyst at ZK Research. “We’re moving to an era where in any given moment, you could have everyone in the office, no one in the office, or every reasonable combination in between,” Kerravala says. “You could have all your shoppers online, only a few, or—depending on your industry—no shoppers online and every possible combination between. The pandemic has created these dramatic shifts in the way we learn, the way we live, and the way we work, based on forces that are outside of anyone’s control.”
When it comes to cloud infrastructure, companies have often pursued half measures—adopting it in such a way as to reinforce old business models, creating private clouds that mimic their on-premises infrastructure. But composability gives enterprises the ability to adapt to changes in operations and in their markets by creating new applications to support needed workflows without hiring additional or outside software developers to implement the changes.
Composable cloud services further liberate companies from relying on running their own software instances solely to customize the code to their needs. Composable applications bring together cloud, customization, integration, and workflow management, allowing companies to be flexible and innovate quickly.
When businesses suffered pandemic disruptions to critical business functions—such as call centers, IT support, and medical administration—composable applications allowed firms to adapt and continue. In one case, a company needed to extend its call-center system, which was hosted in a controlled environment, to allow access to employees through web browsers running on an Amazon virtual machine, says David Lee, vice president of products at RingCentral, an enterprise communications platform that has focused on composability. “They had to make these changes work overnight at employees’ homes, and that was a great challenge for a lot of organizations,” Lee says. “Companies well-adapted to potential change actually made these transitions very easy by composing new applications and workflows.”