Microsoft's newest milestone? World's lowest error rate in speech recognition ZDNet

#artificialintelligence

The techniques Microsoft Research used to achieve a new world-best error rate will eventually enhance the Cortana Windows 10 personal assistant. Microsoft claims to have achieved the world's lowest error rate for speech recognition, as the company jostles with Amazon, Apple, Google, and IBM to develop products that understand speech as well as humans can. According to Microsoft, its speech scientists at Microsoft Research have achieved a word error rate (WER) of just 6.3 percent under an industry-standard evaluation, using techniques that will eventually enhance Cortana. The previous lowest error rate was 6.9 percent, achieved by IBM's Watson team, which beat their own record of eight percent set last year. Both Microsoft and IBM presented papers detailing their work on speech recognition at the Interspeech conference in San Francisco this week, where papers were also presented by Google's speech researchers.


Microsoft's newest milestone? World's lowest error rate in speech recognition ZDNet

#artificialintelligence

The techniques Microsoft Research used to achieve a new world-best error rate will eventually enhance the Cortana Windows 10 personal assistant. Microsoft claims to have achieved the world's lowest error rate for speech recognition, as the company jostles with Amazon, Apple, Google, and IBM to develop products that understand speech as well as humans can. According to Microsoft, its speech scientists at Microsoft Research have achieved a word error rate (WER) of just 6.3 percent under an industry-standard evaluation, using techniques that will eventually enhance Cortana. The previous lowest error rate was 6.9 percent, achieved by IBM's Watson team, which beat their own record of eight percent set last year. Both Microsoft and IBM presented papers detailing their work on speech recognition at the Interspeech conference in San Francisco this week, where papers were also presented by Google's speech researchers.


Microsoft Challenges Google's Artificial Brain With 'Project Adam'

AITopics Original Links

Drawing on the work of a clever cadre of academic researchers, the biggest names in tech--including Google, Facebook, Microsoft, and Apple--are embracing a more powerful form of AI known as "deep learning," using it to improve everything from speech recognition and language translation to computer vision, the ability to identify images without human help. In this new AI order, the general assumption is that Google is out in front. The company now employs the researcher at the heart of the deep-learning movement, the University of Toronto's Geoff Hinton. It has openly discussed the real-world progress of its new AI technologies, including the way deep learning has revamped voice search on Android smartphones. And these technologies hold several records for accuracy in speech recognition and computer vision.


Apple and Its Rivals Bet Their Futures on These Men's Dreams

#artificialintelligence

Over the past five years, artificial intelligence has gone from perennial vaporware to one of the technology industry's brightest hopes. Computers have learned to recognize faces and objects, understand the spoken word, and translate scores of languages. Apple, Facebook, and Microsoft--have bet their futures largely on AI, racing to see who's fastest at building smarter machines. That's fueled the perception that AI has come out of nowhere, what with Tesla's self-driving cars and Alexa chatting up your child. But this was no overnight hit, nor was it the brainchild of a single Silicon Valley entrepreneur. The ideas behind modern AI--neural networks and machine learning--have roots you can trace to the last stages of World War II. Back then, academics were beginning to build computing systems meant to store and process information in ways similar to the human brain. Over the decades, the technology had its ups and downs, but it failed to capture the attention of computer scientists broadly until around 2012, thanks to a handful of stubborn researchers who weren't afraid to look foolish. They remained convinced that neural nets would light up the world and alter humanity's destiny.


Meet the Man Google Hired to Make AI a Reality

AITopics Original Links

Geoffrey Hinton was in high school when a friend convinced him that the brain worked like a hologram. To create one of those 3-D holographic images, you record how countless beams of light bounce off an object and then you store these little bits of information across a vast database. While still in high school, back in 1960s Britain, Hinton was fascinated by the idea that the brain stores memories in much the same way. Rather than keeping them in a single location, it spreads them across its enormous network of neurons. This may seem like a small revelation, but it was a key moment for Hinton -- "I got very excited about that idea," he remembers.