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IBM edges closer to human speech recognition (IBM)

IBM has taken the lead in the race to create speech recognition that's in parity with the error rate of human speech recognition.

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As of last week, IBM’s speech-recognition team achieved a 5.5% error rate, a vast improvement from its previous record of 6.9%.

Digital voice assistants like Apple's Siri and Microsoft's Cortana must meet or outdo human speech recognition — which is estimated to have an error rate of 5.1%, according to IBM — in order to see wider consumer adoption. Voice assistants are expected to be the next major computing interface for smartphones, wearables, connected cars, and home hubs.

While digital voice assistants are far from perfect, competition among tech companies is bolstering overall voice-recognition capabilities, as tech companies vie to outdo one another. IBM is locked in a race with Microsoft, which last year developed a voice-recognition system with an error rate of 5.9%, according to Microsoft's Chief Speech Scientist Xuedong Huang; this beat IBM by an entire percentage point.

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Despite progress, however, existing methods to study voice recognition lack an industry standard. This makes it difficult to truly gauge advances in the technology. IBM tested a combination of “Long Short-Term Memory” (LSTM), a type of artificial neural network, and Google-owned DeepMind’s WaveNet language models, against SWITCHBOARD, which is a series of recorded human discussions. And while SWITCHBOARD has been regarded as a benchmark for speech recognition for more than two decades, there are other measurements that can be used that are regarded as more difficult, like “CallHome," which are more difficult for machines to transcribe, IBM notes. Using CallHome, the company achieved a 10.3% error rate.

Moreover, voice assistants need to overcome several hurdles before mass adoption occurs:

  • They need to surpass “as close as humanly possible." Despite recent advancements, speech recognition needs to reach roughly 95% for voice to be considered the most efficient form of computing input, according to Kleiner Perkins analyst Mary Meeker. That’s because expectations for automated services are much less forgiving than they are for human error. In fact, when a panel of US smartphone owners were asked what they most wanted voice assistants to do better, "understand the words I am saying" received 44% of votes, according to MindMeld.
  • Consumer behavior needs to change. For voice to truly replace text or touch as the primary interface, consumers need to be more willing to use the technology in all situations. Yet relatively few consumers regularly employ voice assistants; just 33% of consumers aged 14-17 regularly used voice assistants in 2016, according to an Accenture Report.
  • Voice assistants need to be more helpful. Opening third-party apps to voice assistants will be key in providing consumers with a use case more in line with future expectations of a truly helpful assistant. Voice assistants like Siri, Google Assistant, and Echo, are only just beginning to gain access to these apps, enabling users to carry out more actions like ordering a car.

The Internet of Things (IoT) is growing rapidly as companies around the world connect thousands of devices every day. But behind those devices, there’s a sector worth hundreds of billions of dollars supporting the IoT.

Platforms are the glue that holds the IoT together, allowing users to take full advantage of the disruptive potential of connected devices. These platforms allow the IoT to achieve its transformational potential, letting businesses manage devices, analyze data, and automate the workflow.

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Peter Newman, research analyst for BI Intelligence, Business Insider's premium research service, has compiled a detailed report on the evolving IoT platform ecosystem. This report sizes the market and identifies the primary growth drivers that will power the IoT platform space in the next five years. It also profiles many of the top IoT platforms by discussing key trends in the platform industry such as platform consolidation.

  • The IoT platforms market is set to expand rapidly in the years to come, with current leading platforms expanding and others entering the space.
  • We define the key categories into which IoT platforms fall: building block open platforms, closed high-end platforms, and product management platforms.
  • We highlight the ways platforms can help companies reach the full five stage potential of the IoT.
  • Explains the coming growth of the IoT platforms.
  • Profiles a number of leading platforms.
  • Highlights the central role platforms play in the IoT.
  • Looks to the future of the IoT platforms market.

Interested in getting the full report? Here are two ways to access it:

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