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    Advancements in AI technology have paved the way for breakthroughs in speech recognition, natural language processing and machine translation. A new startup called Voicery now wants to leverage those same advancements to improve speech synthesis, too. The result is a fast, flexible speech engine that sounds more human — and less like a robot. Its machine voices can then be used anywhere a synthesized voice is needed — including in new applications, like automatically generated audiobooks or podcasts, voice-overs, TV dubs and elsewhere.

    Before starting Voicery, co-founder AndrewGibiansky worked at Baidu Research, where he led the deep learning speech synthesis team.

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    and commercialized its technology in production-quality systems for Baidu.

    Now, Gibiansky is bringing that same skill set to Voicery, where he’s joined by co-founder Bobby Ullman, who previously worked at Palantir on databases and scalable systems.

    “In the time that I was at Baidu, what became very evident is that the revolution in deep learning and machine learning was about to happen to speech synthesis,” explains Gibiansky. “In the past five years, w e’ve seen that these new techniques have brought an amazing gains in computer vision, speech recognition and in other industries — but it hasn’t yet happened with synthesizing human speech. We saw that if we could use this new technology to build speech synthesis engines, we could do it so much better than everything that currently exists.”

    Specifically, the company is leveraging newer deep learning technologies to create better synthesized voices more quickly than before.

    In fact, the founders built Voicery’s speech synthesis engine in just two-and-half months.

    Unlike traditional voice synthesizing solutions, where a single person records hours upon hours of speech that’s then used to create the new voice,Voicery trains its system on hundreds of voices at once.

    It also can use varying amounts of speech input from any one person. Because of how much data it takes in, the system sounds more human as it learns the correct pronunciations, inflections and accents from a wider variety of source voices.

    The company claims its voices are nearly indistinguishable from humans — it even published a quiz on its website that asks visitors to see if they can identify which ones are synthesized and which are real. I found that you’re still able to identify the voices as machines, but they’re much better than the machine reader voices you may be used to.

    Of course, given the rapid pace of technology development in this field — not to mention the fact that the team built their system in a matter of months — one has to wonder why the major players in voice computing couldn’t just do something similar with their own in-house engineering teams.

    However, Gibiansky says that Voicery has the advantage of being the first out of the gate with its technology that capitalizes on the machine learning advancements.

    “Noneof the currently published research is quite good enough for what we wanted to do, so we had to extend that a fair bit,” he notes. “Now we have several voices that are ready, and we’re starting to find customers to partner with.”

    Voicery already has a few customers piloting the technology, but nothing to announce at this time as those talks are in various stages.

    The company is charging customers an upfront fee to develop a new voice for a customer, and then charges a per-usage fee.

    The technology can be used where voice systems exist today, like in translation apps, GPS navigation apps, voice assistant apps or screen readers, for example. But the team also sees the potential for it to open up new markets, given the ease of creating synthesized voices that really sound like people. This includes things like synthesizing podcasts, reading the news (think: Alexa’s “Flash Briefing”), TV dub-ins, voices for characters in video games and more.

    “We can move into spaces that fundamentally haven’t been using the technology because it hasn’t been high enough quality. And we have some interest from companies that are looking to do this,” saysGibiansky.

    Voicery, based in San Francisco, is bootstrapped save for the funding it received by participating in Y Combinator’s Winter 2018 class. It’s looking to raise additional funds after YC’s Demo Day.

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    Game of Thrones leads the nominations at this year's Emmy Awards, after being ineligible in 2017.

    The HBO series has 22 nominations in total, followed by sci-fi series Westworld and comedy show Saturday Night Live, both with 21.

    It is the first time in 18 years that HBO did not have the highest number of Emmy nominations.

    Netflix leads with a total of 112 nominations, beating HBO, which received 108.

    In 2017, The Handmaid's Tale became the first show from a streaming platform to receive the award for best drama.

    This year several actresses from the dystopian drama have received nominations, including Elisabeth Moss and Alexis Bledel.

    Several British actors have received nominations for the awards also.

    Millie Bobby Brown is up for the best supporting actress award for her performance in Netflix's Stranger Things.

    Claire Foy, from HBO's royal drama The Crown, is nominated for the best actress award alongside her cast mates Matt Smith and Vanessa Kirby, who were nominated for the best supporting actor and best supporting actress awards.

    Benedict Cumberbatch is nominated for Patrick Melrose.

    The Late Late Show with James Corden is up for the outstanding variety talk show award.

    Key categories:

    Best lead actress in a drama series

    Best lead actor in a drama series

    Best lead actress in a limited series or movie

    Best lead actor in a limited series or movie

    Best lead actor in a comedy series

    Best lead actress in a comedy series

    Best drama series

    Best comedy series

    Best limited series

    Best TV movie

    Comedy show Saturday Night Live's Michael Che and Colin Jost are set to host this years awards, on 17 September.

    The full nominations are on the Emmys website.

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    Last updated: May 27, 2018

    We’ve all seen it before—the pocket knife that you couldn’t cut warm butter with on a hot July afternoon. It’s a little rusty, the joints are gunked up with who-knows-what, and the only thing it’s good for is opening letters. Almost as bad (or worse depending on your viewpoint) are the kitchen knives that can’t cut tomatoes, or anything remotely tough without repeated sawing.There’s no reason it has to be this way. I think sharpening edged tools is one of the more useful outdoor skills, and it has a glorious payoff in the home as well. The good news is that it’s no longer an art practiced exclusively by mountain men who eat only bear meat. The old days of nothing but Arkansas stones and a little luck are over. It’s really not hard at all; you just need the right equipment.

    Let’s start with knives.

    Sharpening Knives

    The essential sharpening process isn’t rocket science. With an abrasive material, you remove a small amount of metal to restore a clean, sharp edge, and you remove this metal using a low-friction environment so heat build-up doesn’t destroy the temper of your blade.

    This isn’t meant to be a piece on metallurgy.There are people way geekier than I who can give you a lesson on the finer points of the hundreds of different alloys with their various properties. It’s just about sharpening stuff.

    My preference in a good knife is a high carbon content. Super-high carbon content knives are almost always not stainless, but will discolor over time to a dull gray. I happen to think they look beautiful, but that’s my opinion. They do rust if they are kept damp, but a little oil and a little care keeps them from rusting. Goat cheese will darken your knife immediately, so if you want to get a good patina on the blade, just slice off a hunk for your bagel.

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