Steve Young (software engineer)

Stephen John Young CBE FRS FREng (born 1951) is a British researcher,[1] Professor of Information Engineering at the University of Cambridge and an entrepreneur. He is one of the pioneers of automated speech recognition[2] and statistical spoken dialogue systems.[3][4] He served as the Senior Pro-Vice-Chancellor of the University of Cambridge from 2009 to 2015, responsible for planning and resources. From 2015 to 2019, he held a joint appointment between his professorship at Cambridge and Apple, where he was a senior member of the Siri development team.[5]

Steve Young

CBE FRS FREng
Born
Stephen John Young

1951 (age 71–72)
Liverpool, United Kingdom
Alma materUniversity of Cambridge
Known for
Scientific career
Fields
Institutions
ThesisSpeech synthesis from concept with applications to speech output from systems (1978)
Doctoral advisorFrank Fallside
Websitemi.eng.cam.ac.uk/~sjy

Early life and education

Young was born in Liverpool on 23 January 1951. He studied at the University of Cambridge, completing a BA in Electrical Sciences in 1973 and a PhD in speech recognition in 1978, under the supervision of Professor Frank Fallside at the Engineering Department. He held lectureships at both Manchester and Cambridge before being elected to the Chair of Information Engineering at Cambridge University in 1994.[6]

Research and academic career

He is best known as the leading author of the HTK toolkit,[2] a software package for using hidden Markov models to model time series, mainly used for speech recognition. Its first version was originally developed by Young at the Machine Intelligence Laboratory of the Cambridge University Engineering Department (CUED) in 1989. Due to the growing popularity of the toolkit worldwide, Microsoft decided to make the core HTK toolkit available again and licensed the software back to CUED after its acquisition of Entropic, the startup Steve co-founded in 1993 to distribute and maintain the HTK toolkit. The HTK book,[7] which is the tutorial of the HTK toolkit, has received more than 7,000 citations.[8]

In the late nineties, Young's research interests shifted to the design of statistical spoken dialogue systems. His most notable contribution to the field is the partially observable Markov decision process (POMDP) based dialogue management framework,[3][9][10] which includes the Hidden Information State (HIS) dialogue model,[11] the first practical dialogue management model based on the POMDP framework. His research focuses on developing spoken dialogue systems that are robust against noise introduced by noisy speech recognisers, as well as adapt and scale on-line in interaction with real users. One notable instance of this approach is the application of Gaussian process based reinforcement learning for rapid policy optimisation.[12][13] In recent years, Young's research group has successfully applied deep learning techniques to various submodules of statistical dialogue systems,[14][15][16][17] winning multiple best paper awards at prestigious speech and NLP conferences.

Entrepreneurship

Apart from his academic and scientific contributions, Young is also a successful entrepreneur and he took a leading role in three company acquisitions:

  • Entropic, a speech recognition software company that developed applications for voice-enabling the web via mobile operators. The company was acquired by Microsoft in 1999.[18]
  • Phonetic Arts, a speech synthesis company that delivered technology for generating natural expressive speech. The technology developed by the company allowed computer games to say various sentences with different kinds of voices. Phonetic arts was acquired by Google in 2010.[18]
  • VocalIQ, a dialogue technology company that built the world's first dialogue system application programming interface. The company's technology provided a platform for voice interfaces, allowing businesses to voice-enable mobile devices and proprietary apps. VocalIQ was acquired by Apple in 2015.[18]

Awards and honours

Young is a Fellow of the Royal Academy of Engineering,[19] the Institution of Engineering and Technology (IET), the Institute of Electrical and Electronics Engineers (IEEE), the RSA and the International Speech Communication Association (ISCA).[5]

He received the IEEE Signal Processing Society Technical Achievement Award in 2004, and the ISCA Medal for Scientific Achievement in 2010. He also received the European Signal Processing Society Individual Technical Achievement Award in 2013, and the IEEE James L Flanagan Speech and Audio Processing Award in 2015.[5]

In 2020 he was elected a Fellow of the Royal Society (FRS) [20]

Young was appointed Commander of the Order of the British Empire (CBE) in the 2022 Birthday Honours for services to software engineering.[21]

References
  1. "Steve Young – Google Scholar Citations". Google Scholar. Retrieved 2 May 2017.
  2. "HTK Speech Recognition Toolkit". University of Cambridge.
  3. Williams, Jason; Young, Steve (2007). "Partially observable Markov decision processes for spoken dialogue systems" (PDF). Computer Speech and Language. 21 (2): 393–422. doi:10.1016/j.csl.2006.06.008. S2CID 13903063.
  4. Young, Steve; et al. "The Hidden Information State model: A practical framework for POMDP-based spoken dialogue management" (PDF). Computer Speech and Language.
  5. "Professor Steve Young, Professor of Information Engineering". University of Cambridge.
  6. "Stephen Young, Emmanuel Fellow".
  7. Young, Steve. "The HTK book" (PDF). Cambridge University Engineering Department.
  8. "Google Scholar". Retrieved 23 December 2020.
  9. Blaise Thompson and Steve Young (2010). "Bayesian update of dialogue state: A POMDP framework for spoken dialogue systems" (PDF). Computer Speech and Language.
  10. Young, Steve (2013). "POMDP-based Statistical Spoken Dialogue Systems: a Review" (PDF). Proc IEEE.
  11. Steve Young; et al. (2010). "The Hidden Information State Model: a practical framework for POMDP-based spoken dialogue management" (PDF). Computer Speech and Language.
  12. Milica Gasic and Steve Young (2014). "Gaussian processes for POMDP-based dialogue manager optimization" (Document). IEEE Trans. Audio, Speech and Language Processing.
  13. Pei-Hao Su; et al. (2016). "On-line Active Reward Learning for Policy Optimisation in Spoken Dialogue Systems" (PDF). Proc ACL. arXiv:1605.07669.
  14. Lina Rojas-Barahona; et al. (2016). "Exploiting Sentence and Context Representations in Deep Neural Models for Spoken Language Understanding". Proc Coling. pp. 258–267.
  15. Nikola Mrkšić; et al. (2017). "The Neural Belief Tracker: Data-Driven Dialogue State Tracking" (PDF). Proc ACL.
  16. Tsung-Hsien Wen; et al. (2015). "Semantically Conditioned LSTM-based Natural Language Generation for Spoken Dialogue Systems" (PDF). Proc EMNLP. arXiv:1508.01745.
  17. Tsung-Hsien Wen el al (2017). "A Network-based End-to-End Trainable Task-oriented Dialogue System". arXiv:1604.04562 [cs.CL].
  18. "Steve Young: Executive Profile & Biography". Bloomberg L.P.
  19. "Stephen Young". Royal Academy of Engineering. Retrieved 23 December 2020.
  20. "Stephen Young". Royal Society. Retrieved 20 September 2020.
  21. "No. 63714". The London Gazette (Supplement). 1 June 2022. p. B11.


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