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Deng receives prestigious IEEE Technical Achievement Award

December 3, 2015 | By Microsoft blog editor

By George Thomas Jr., Writer, Microsoft

Li Deng - IEEE SPS Technical Achievement Award

Adding to an already lengthy list of accolades, Li Deng, partner research manager in Microsoft’s Redmond, Wash. lab, has received the 2015 IEEE Signal Processing Society Technical Achievement Award for outstanding contributions to deep learning and to automatic speech recognition.

The award honors a person, who over a period of years, has made outstanding technical contributions to theory and/or practice in the technical areas within the scope of society, as demonstrated by publications, patents, or recognized impact on the field.

“I am honored and humbled to receive this award from my IEEE organization,” Deng says.

But, he adds, he had a lot of help.

“Many collaborators, in Microsoft as well as at universities, have been working closely with me on developing deep learning technology and applying it to a range of applications including notably automatic speech recognition, language processing, and business data analytics,” Deng says. “They share this honor by the amazing teamwork exhibited for many years.”

In 2013 Deng received the IEEE SPS Best Paper Award for Context-Dependent Pre-trained Deep Neural Networks for Large Vocabulary Speech Recognition, along with colleagues George Dahl, Dong Yu and Alex Acero.

“The idea of using deep neural nets for speech recognition was pioneered by Li Deng and his collaborators back in 2009,” notes Peter Lee, corporate vice president, Microsoft Research. “At that time, almost no one thought that this would be a good idea — in fact, I personally thought it was nuts!

“But within 18 months it became clear that this would be a transformational advance, not only in speech recognition but in a wide range of classification and perception problems. Li can truly be called a pioneer in the field,” Lee says.

Deng joined Microsoft Research in 1999 and his recent research has focused on deep learning and machine intelligence applied to big text data and speech processing, speech-to-speech translation, information retrieval and data mining. The breadth of his research is far reaching and extends into numerous areas of multimodal human-computer interactions.

He has published more than 300 referred papers in leading journals and conferences and authored or co-authored five books in the areas of speech technology, machine learning, and other areas of computer science, including Deep Learning: Methods and Applications and Automatic Speech Recognition: A Deep Learning Approach.

The IEEE SPS is the largest technical community for research in machine learning for signal processing, speech recognition, image processing, language understanding, and other areas of information processing. Deng will accept the award at the IEEE International Conference on Acoustics, Speech and Signal Processing in Shanghai, China in March 2016.

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