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These advances have carried over to personalization. And to this analysis the Google app can add data from billions of search queries, “to better predict what you're probably saying.” The recent arrival of Google Voice Search for the iPhone demonstrates an ability to offload the processing for the app to cloud data centers to perform the large-scale data analysis necessary. The technology improved steadily from that point - with the past two years seeing a dramatic improvement due to commercial speech recognition technologies driven by deep learning approaches combined with massive data sets.Īs Speech Recognition Through the Decades explains, the bottleneck with speech recognition has always been the availability of data, and the ability to process it efficiently.

When DragonNaturallySpeaking was released in 1997 it could understand natural speech at about 100 words per minute. Speech recognition blossomed with advanced processing capabilities in the 1990s.

Harpy could understand 1011 words, approximately the vocabulary of an average three-year-old. In the 1970s, the DARPA Speech Understanding Research program was responsible for Carnegie Mellon's 'Harpy' speech-understanding system. Ten years later, IBM demonstrated a machine at the World's Fair that could understand 16 words spoken in English. In 1952, Bell Laboratories designed the 'Audrey' system, which recognized digits spoken by a single voice. Who hasn’t experienced the infinite loop of “Please repeat, I did not understand your response”?Īt first, speech recognition systems could only understand digits. Just as with speech synthesis, speech recognition technology has come a long way, though many would say the Interactice Voice Response (IVR) systems we deal with daily remain medieval. Advances since then have taken advantage of increased computer power to create much more natural sounding synthetic voices, and now have reached close to perfection using powerful concatenative and formant synthesis approaches. Mobile electronics featuring speech synthesis began emerging in the 1970s. For decades one of the most well known was DECTalk with its recognizable, inaccurate and slightly inebriated robotic cadence often characterized as sounding like a “drunken Swede.” The first computer-based speech synthesis systems were created in the late 1900s with notable contributions from IBM, Bell Labs and Digital Equipment Corporation. The 12th and 13th centuries boast even earlier legendary speech synthesizers - “brazen heads” fashioned of brass or bronze, whether mechanical or perhaps magical. It notably provided important data to early studies of phonetics. One of the earliest attempts at synthetic speech occurred in the 18th century, when Wolfgang von Kempelen’s wood and leather speaking machine generated audible speech. And Amazon has released its smart Echo appliance that converses with you to execute your every command.

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Google Searches for its Future posits that based on the market move to mobile, Google is facing the biggest shift since its founding: “If Google doesn’t figure out how to make the perfect virtual assistant, another tech company will.”Īpple’s Siri is already automatically installed on hundreds of millions of iPhones and the Apple Watch. Microsoft’s Cortana is an integral part of its new operating system, Windows 10. Essentially all are attempting to teach computers to better understand and respond to the world the way (smart) humans do.

Technology companies like Google are not only investing in data collection and analytics to ensure information response quality, but also investing in voice recognition and text-to-speech advances. Google’s database of “500 million things it knows about the world” is extensive and dynamic, constantly being updated by web crawlers. In a Slate article, Google’s VP of engineering Scott Huffman explains that deriving intelligence from information is a core part of Google’s mission as a company. There’s a reason that Google Voice Search is so smart.