no code implementations • 2 Jun 2020 • A. Backis, A. Khaplanov, R. Al Jebali, R. Ammer, I. Apostolidis, J. Birch, C. -C. Lai, P. P. Deen, M. Etxegarai, N. de Ruette, J. Freita Ramos, D. F. Förster, E. Haettner, R. Hall-Wilton, D. Hamilton, C. Höglund, P. M. Kadletz, K. Kanaki, E. Karnickis, O. Kirstein, S. Kolya, Z. Kraujalyte, A. Laloni, K. Livingston, O. Löhman, V. Maulerova, N. Mauritzon, F. Müller, I. Lopez Higuera, T. Richter, L. Robinson, R. Roth, M. Shetty, J. Taylor, R. Woracek, W. Xiong
Furthermore, it is to characterize differences between the detector technologies in terms of internal scattering, as well as the time reconstruction of ~ $\mu$s short neutron pulses.
Instrumentation and Detectors
no code implementations • 21 Aug 2017 • W. Xiong, L. Wu, F. Alleva, J. Droppo, X. Huang, A. Stolcke
We describe the 2017 version of Microsoft's conversational speech recognition system, in which we update our 2016 system with recent developments in neural-network-based acoustic and language modeling to further advance the state of the art on the Switchboard speech recognition task.
no code implementations • 17 Oct 2016 • W. Xiong, J. Droppo, X. Huang, F. Seide, M. Seltzer, A. Stolcke, D. Yu, G. Zweig
Conversational speech recognition has served as a flagship speech recognition task since the release of the Switchboard corpus in the 1990s.
Ranked #4 on Speech Recognition on Switchboard + Hub500
no code implementations • 12 Sep 2016 • W. Xiong, J. Droppo, X. Huang, F. Seide, M. Seltzer, A. Stolcke, D. Yu, G. Zweig
We describe Microsoft's conversational speech recognition system, in which we combine recent developments in neural-network-based acoustic and language modeling to advance the state of the art on the Switchboard recognition task.
Ranked #4 on Speech Recognition on swb_hub_500 WER fullSWBCH