The famous physicist Stephen Hawking has achieved great success in scientific research, but unfortunately, because of the serious motor neuron disease in his youth, he has only been able to use a customized set of wheelchairs for many years. The communication system communicates with others. Now, in order to improve communication efficiency, Professor Hawking has also begun to use smart input methods.
Since the communication system used by Stephen Hawking is customized, placing the smart input method into this communication system is not as simple as installing a software package. With Intel's opportunity to overhaul Hawking's communications system, input method vendor SwiftKey was able to integrate its technology into the system.
Since there are many input method products on the market, each input method will try to find a "selling point" for itself. SwiftKey gives itself a "selling point" that it will learn the user's input habits and then construct the corresponding language model. Improve efficiency. Before SwiftKey was integrated into Professor Hawking's communications system, SwiftKey's technical team first asked it to learn about Stephen Hawking's published and unpublished portfolios. In this process, machine learning technology also builds a set of Steven Hawking-style language models.
Just as we usually speak, we have our own mantras and common words. When using keyboard input, we follow the language style that has already formed in our minds. In this way, when the computer learns this style, it can of course predict what the user wants to input next and where the error is.
So what is the biggest difficulty in integrating this smart input method into Steven Hawking's communication system? In the opinion of SwiftKey's technical director Joe Osborne, the biggest problem is that Professor Hawking's spelling is too accurate. Unlike users who often make typos on their mobile phones, Stephen Hawking's spelling is not so bad, which in some ways leads to some nowhere in SwiftKey's error correction technology. This is definitely a special case for SwiftKey.
Joe Osborne believes that technology should be able to adjust to meet user needs, rather than allowing users to adapt to technology, so SwiftKey will consider the accuracy of user interaction with the keyboard, the user's most important attention is predictive technology or error correction, users How to use the language in your own way. When the technology based on the user's needs is more adaptable, the technical assistance will naturally become stronger.
With this intelligent input prediction and error correction system, Stephen Hawking's speech speed naturally naturally increased, the test results show that the overall speed has almost doubled, and the machine learning mode will continue to optimize the process. .
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