Advisory Board

Prof. Hynek Hermansky

Johns Hopkins University

Hynek Hermansky is the Julian S. Smith Professor of the Electrical Engineering and the Director of Center for Language and Speech Processing at the Johns Hopkins University in Baltimore, Maryland, and a Research Professor at the Brno University of Technology, Czech Republic. His main research interests are in bio-inspired speech processing. He has been working in speech research for over 30 years, previously as a Director of Research at the IDIAP Research Institute, Martigny and a Titular Professor at the Swiss Federal Institute of Technology in Lausanne, Switzerland, a Professor and Director of the Center for Information Processing at OHSU Portland, Oregon, a Senior Member of Research Staff at U S WEST Advanced Technologies in Boulder, Colorado, a Research Engineer at Panasonic Technologies in Santa Barbara, California, a Research Fellow at the University of Tokyo, and an Assistant Professor at the Brno University of Technology, Czech Republic.  He is a Fellow of IEEE, a Fellow of International Speech Communication, and an External Fellow of the International Computer Science Institute in Berkeley, California. He is also the holder of the 2013 International Speech Communication Association Medal for Scientific Achievement, is a Member of The Board of the International Speech Communication Association, and a Member of the Editorial Board of Speech Communication. He was the General Chair of the 2013 ICASSP Workshop on Automatic Speech Recognition and Understanding, a Member of the Organizing Committee at the 2011 ICASSP in Prague, Technical Chair at the 1998 ICASSP in Seattle and an Associate Editor for IEEE Transaction on Speech and Audio. He holds 10 US patents and authored or co-authored over 250 papers in reviewed journals and conference proceedings. Prof. Hermansky holds Dr.Eng. degree from the University of Tokyo, and Dipl. Ing. degree from Brno University of Technology, Czech Republic.

Prof. Shri Narayanan

University of Southern California

Shrikanth (Shri) Narayanan is Andrew J. Viterbi Professor of Engineering at the University of Southern California, where he is Professor of Electrical Engineering, and jointly in Computer Science, Linguistics, Psychology, Neuroscience and Pediatrics, and Director of the Ming Hsieh Institute. Prior to USC he was with AT&T Bell Labs and AT&T Research. His research focuses on human-centered information processing and communication technologies. He is a Fellow of the Acoustical Society of America, IEEE, and the American Association for the Advancement of Science (AAAS). Shri Narayanan is the incoming Editor in Chief for IEEE Journal on Selected Topics in Signal Processing, an Editor for the Computer, Speech and Language Journal and an Associate Editor for the IEEE Transactions on Affective Computing, the Journal of Acoustical Society of America, IEEE Transactions on Signal and Information Processing over Networks, and the APISPA Transactions on Signal and Information Processing having previously served an Associate Editor for the IEEE Transactions of Speech and Audio Processing (2000-2004), the IEEE Signal Processing Magazine (2005-2008) and the IEEE Transactions on Multimedia (2008-2012). He is a recipient of several honors including the 2015 Engineers Council’s Distinguished Educator Award, the 2005 and 2009 Best Transactions Paper awards from the IEEE Signal Processing Society and serving as its Distinguished Lecturer for 2010-11, and as an ISCA Distinguished Lecturer for 2015-16. With his students, he has received a number of best paper awards including a 2014 Ten-year Technical Impact Award from ACM ICMI and Interspeech Challenges in 2009 (Emotion classification), 2011 (Speaker state classification), 2012 (Speaker trait classification), 2013 (Paralinguistics/Social Signals), 2014 (Paralinguistics/Cognitive Load) and in 2015 (Non-nativeness detection). He has published over 650 papers and has been granted 17 U.S. patents.

Dr. Daniel Povey

Johns Hopkins University

Daniel Povey completed his PhD at Cambridge University in 2003, and after spending just under ten years working for industry research labs (IBM Research and then Microsoft Research), joined Johns Hopkins University in 2012. His thesis work introduced several practical innovations for discriminative training of models for speech recognition, and made those techniques widely popular. At IBM Research he introduced feature-space discriminative training, which has become a common feature of state-of-the art systems. He also devised the Subspace Gaussian Mixture Model– a modeling technique which enhances the Gaussian Mixture Model framework by using subspace ideas similar to those used in speaker identification. At Microsoft Research and then at Johns Hopkins University, he has been creating a speech recognition toolkit “Kaldi”, which aims to make state-of-the-art speech recognition techniques widely accessible.

Dr. Alexander Waibel

Carnegie Mellon University & Karlsruhe Institute of Technology, Germany

Alexander Waibel is a Professor of Computer Science at Carnegie Mellon University, Pittsburgh and at the Karlsruhe Institute of Technology, Germany.  He is the director of the International Center for Advanced Communication Technologies (interACT). The Center works internationally in a network of eight top research institutions.  Its mission is to develop multimodal and multilingual human communication technologies that improve human-human and human-machine communication.  Prof. Waibel’s team developed and demonstrated a first speech translation systems in Europe&USA (1990/1991 (ICASSP’91)), the first simultaneous lecture translator (2005), and Jibbigo, the first commercial speech translator on a phone.

Dr. Waibel was a founder and served as chairmen of C-STAR, the Consortium for Speech Translation Advanced Research in 1991. Waibel also served as co-director of IMMI, a joint venture between KIT, CNRS & RWTH. He directed and coordinated many research programs in speech, translation, multimodal interfaces and machine learning in the US, Europe and Asia, including large US-DARPA and European multi-site Integrated Projects. Recent large projects include EU-BRIDGE (speech translation services in Europe) and CHIL (Computers in the Human Interaction Loop) for implicit computer interaction in multimodal smart rooms.

Prof. Yonghong Yan

Chinese Academy of Sciences

Prof. Yonghong Yan holds over 50 patents and has published over 200 peer reviewed papers. He is an executive committee member of the Chinese Acoustics Society, associate editor-in-chief of Applied Acoustics, and editorial board member of Journal of Acoustics and Journal of Computer Science & Technology. He was selected as an outstanding young scholar of the Hundred Talents Program in 2002. He was awarded Chinese NSF Distinguished Young Scientist in 2009.

Prof. James F. Allen

University of Rochester

My research interests span a range of issues covering natural language understanding, discourse, knowledge representation, common-sense reasoning and planning. I am particularly interested in the overlap between natural language understanding and reasoning. While most of the NLP field has moved to statistical learning methods as the paradigm for language processing, I believe that deep language understanding can only currently be achieved by significant hand-engineering of semantically-rich formalisms coupled with statistical preferences. For further discussion of this viewpoint, see the state of NLP . For a more general discussion of AI, see my keynote address from the 1998 AAAI National conference here . The TRIPS project is a long-term effort to build generic technology for dialogue systems (both spoken and ‘chat’ systems), which we have now pursued for over a decade. This includes broad-coverage domain-general natural language processing, dialogue agents built using models of collaborative problem solving, dynamic context-sensitive language modeling, and a rich engineering framework for building dialogue systems in new domains in short times. We can build robust spoken dialogue systems in significantly less time than it would take to collect and annotate a small starter corpora that would be needed for machine-learning driven approaches.

Prof. Barbara J. Grosz

Harvard University

Barbara J. Grosz is Higgins Professor of Natural Sciences in the School of Engineering and Applied Sciences at Harvard University. Her many seminal contributions to Artificial Intelligence (AI) include establishing the research field of computational modeling of discourse, developing some of the earliest computer dialogue systems, pioneering models of collaboration, and the development of collaborative multi-agent systems and collaborative systems for human-computer communication.  Grosz is a member of the National Academy of Engineering, the American Philosophical Society, and the American Academy of Arts and Sciences and a corresponding fellow of the Royal Society of Edinburgh, and she is a fellow of the Association for the Advancement of Artificial Intelligence (AAAI), the Association for Computing Machinery (ACM) and the American Association for the Advancement of Science.  She is recipient of the University of California, Berkeley Distinguished Alumna Award in Computer Sciences and Engineering (1997), the ACM/AAAI Allen Newell Award (2009), and the 2015 IJCAI Research Excellence Award.

Prof. Henry Kautz

University of Rochester

Henry Kautz is the Robin & Tim Wentworth Director of the Goergen Institute for Data Science and Professor in the Department of Computer Science at the University of Rochester. He has served as department head at AT&T Bell Labs in Murray Hill, NJ, and as a full professor at the University of Washington, Seattle. In 2010 he was elected President of the Association for Advancement of Artificial Intelligence (AAAI). His research in artificial intelligence, pervasive computing, and healthcare applications has led him to be honored as a Fellow of the American Association for the Advancement of Science (AAAS), Fellow of the Association for Computing Machinery (ACM), and Fellow of the AAAI. He holds the Computers & Thought Award from the International Joint Conference on Artificial Intelligence. In 2013, he received the Ubicomp 10-Year Impact award for his paper “Inferring High-level Behavior from Low-level Sensors”.

Prof. Martha Palmer

University of Colorado

Prof. Martha Palmer holds joint appointments in Linguistics and Computer Science departments at the University of Colorado, and directed the international Linguistic Institute 2011. She is an ACL Fellow. Her research has focused on capturing elements of the meanings of words that can comprise automatic representations of complex sentences and documents. She and her students produce linguistic annotations and are also engaged in training automatic annotators, funded by NSF, NIH and DARPA.  She is an editor of Linguistic Issues in Language Technology, and has been on the Editorial Board of Computational Linguistics and a co-Editor of the Journal of Natural Language Engineering.

Prof. Mark Steedman

University of Edinburgh

Mark Steedman has been Professor of Cognitive Science in the School of Informatics at the University of Edinburgh since 1998. Previously, he was Professor in the Department of Computer and Information Science at the University of Pennsylvania, which he joined as Associate Professor in 1988, after teaching at the Universities of Warwick and Edinburgh. His PhD is in Artificial Intelligence from the University of Edinburgh. He was a Alfred P. Sloan Fellow at the University of Texas at Austin in 1980/81, and a Visiting Professor at Penn in 1986/87. He is a Fellow of the American Association for Artificial Intelligence, the Royal Society of Edinburgh, the British Academy, the Association for Computational Linguistics, and the Cognitive Science Society, and a Member of the European Academy.

His research interests cover issues in computational linguistics, artificial intelligence, computer science and cognitive science, including syntax and semantics of natural languages and programming languages, wide-coverage semantic parsing, comprehension of natural language discourse by humans and by machine, grammar-based language modeling, natural language generation, and intonation in spoken discourse. Much of his current NLP research is addressed to probabilistic parsing and issues in spoken discourse and dialogue using the CCG grammar formalism, especially the semantics of intonation and the acquisiton of language by child and machine. He sometimes works with colleagues in computer animation using these theories to guide the graphical animation of speaking virtual or simulated autonomous human agents. Some of his research concerns the analysis of music by humans and machines.

Prof. David Traum

University of Southern California

Dr. David Traum is the director of Natural Language Research at the Institute for Creative Technologies (ICT) and a Research Faculty member of the Department of Computer Science at the University of Southern California (USC).  He leads the Natural Language Dialogue Group at ICT, which currently consists of seven Ph.D.s, and several students. More information about the group can be found here:  Traum’s research focuses on Dialogue Communication between Human and Artificial Agents.  He has engaged in theoretical, implementational and empirical approaches to the problem, studying human-human natural language and multi-modal dialogue, as well as building a number of dialogue systems to communicate with human users. Traum has authored over 200 refereed technical articles, is a founding editor of the Journal Dialogue and Discourse, has chaired and served on many conference program committees, and is a past President and current board member of SIGDIAL, the international special interest group in discourse and dialogue.  Traum earned his Ph.D. in Computer Science at the University of Rochester in 1994.

Prof. Bonnie Webber

University of Edinburgh

Bonnie Webber is Deputy Head of the School of Informatics, University of Edinburgh. She works on Natural Language Processing, and contributes to the University’s growing presence in Bioinformatics. Her current research interests include problems of terminology and text mining, as well as long-standing interests in question answering and anaphor resolution in discourse.

Prof. Dan Weld

University of Washington

Daniel S. Weld is Thomas J. Cable / WRF Professor of Computer Science & Engineering at the University of Washington and an Entrepreneurial Faculty Fellow. After formative education at Phillips Academy, he received bachelor’s degrees in both CS and Biochemistry at Yale University in 1982. He landed a Ph.D. from the MIT Artificial Intelligence Lab in 1988, received a Presidential Young Investigator’s award in 1989, an Office of Naval Research Young Investigator’s award in 1990, was named AAAI Fellow in 1999 and deemed ACM Fellow in 2005. Dan was a founding editor for the Journal of AI Research, was area editor for the Journal of the ACM, guest editor for Computational Intelligence and Artificial Intelligence, and was Program Chair for AAAI-96. Dan has published two books and scads of technical papers. Dan is an active entrepreneur with several patents and technology licenses. He co-founded Netbot Incorporated, creator of Jango Shopping Search (acquired by Excite), AdRelevance, a monitoring service for internet advertising, (acquired by Media Metrix), Nimble Technology, a data integration company (acquired by Actuate). Dan is a Venture Partner at the Madrona Venture Group, and a member of the Technical Advisory Boards for the Allen Institute for Artificial Intelligence, Context Relevant, Spare5, and Madrona.

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