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DIGITAL DICTATION, DOCUMENTS & DATA
Big data helping speech recognition become mainstream
Steve Young, Professor of Information Engineering at the University of Cambridge, and a global expert in speech recognition technologies, gives his thoughts on the advances and challenges facing this ‘growing’ research area. David Stevenson reports.
of the Institute of Electrical and Electronics Engineers (IEEE) James L Flanagan Speech and Audio Processing Award.
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The annual prize is given to an individual or small team for “an outstanding contribution to the advancement of speech and/or audio signal processing”. For the last 35 years, Young, who is Professor of Information Engineering at the University, has focused his attention on developing systems that allow humans to interact with machines using voice.
He told NHE that research in this area made steady but not spectacular progress from the mid-1980s to the mid-2000s. “But over the last five to 10 years we’ve seen really quite significant acceleration in progress,” he said. “And that is why we are now seeing speech recognition coming into the mainstream with services like Apple Siri and Google Now, and the new smart watches that do speech recognition.”
Prof Young, who is the senior pro-vice- chancellor responsible for planning and resources at Cambridge, added that modern systems are built on the notion of building statistical models that represent the data.
72 | national health executive Sep/Oct 14
niversity of Cambridge’s Professor Steve Young will be the 2015 recipient
“So the way you build a speech recogniser, essentially, is that you get some data, which is people speaking, you transcribe the data and then you try to model the data and find a way to automatically generate the transcriptions yourself – and then you have a speech recogniser,” he said. “The key to all of that is some quite sophisticated statistical modelling algorithms and the availability of the data.”
Big data
The expert told us that it is the nature of data, and its wide availability nowadays, that has changed the speech recognition landscape. “When you speak into your phone, the signal is being routed to a server farm somewhere in North Virginia if you’re Apple or the Arizona desert if you’re Google, and it is being processed there and the result is being fed-back to your phone,” said Prof Young.
This allows two things to happen. Firstly, it unleashes the possibility of using some very powerful computing to recognise people’s voices. Then secondly, and more importantly, the companies are capturing the data.
“When Siri was first launched, for example, it wasn’t that great,” said Prof Young, “but as
more people started using it the company was capturing huge amounts of data. And then by using and collecting the data and upgrading the models, people found the recognition improved so they used the system more, so they gave more data. That has happened over a wide range of fields, and it is the ‘big data’ paradigm that we are hearing a lot about.”
He added that the internet is also allowing organisations, be it research or commercial, to collect huge datasets and do things that they could never do before, and that is what has led to a rapid improvement in performance and an “explosion of interest” in the field.
“It is nice, looking back, that we’ve had these bursts of speech recognition research being a very hot topic, then people being disillusioned with it and it going out of fashion, and then coming back,” added Prof Young. “And we are in one of those phases where it is back and people are very interested, especially with the big players investing huge amounts in improving services.”
Dictation and voice recognition in healthcare
Dictation in the medical area has been one
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