at the Arabic Language Technologies group (ALT) at the Qatar Computing Research Institute (QCRI). His work interests are in the area of speech recognition with special attention to dialectal Arabic speech and text processing.
Ahmed completed his PhD at the University of Edinburgh and BSc at Cairo University.
Principal Research Manager
of the Conversation Understanding Sciences group at Microsoft AI+R, in charge of dialog systems and language understanding technology for the digital assistant Cortana. Prior to joining Microsoft in 2012, Imed was a Senior Researcher at IBM for almost a decade, where he led several Multilingual NLP projects, including Arabic NLP, informatics extraction, semantic role labeling, language modeling and machine translation. Prior to IBM, Imed was a researcher at Bell Labs, Lucent Technologies, for almost half dozen years working on speech recognition, language modeling and spoken dialog systems. Imed received his M.Sc. and Ph.D. from the University-of-Nancy1 in France. He also obtained a MEng degree in computer science from ENSI in Tunisia. Imed is a senior member of IEEE, served as a member of the IEEE Speech and Language Processing Technical Committee, and is the associate editor of IEEE Trans. on Audio, Speech and Language Processing as well as TALLIP ACM journals. He is also the Information Officer of the ACL SIG on Semitic-Languages and served as chair as well as reviewing-committee-member of several conferences and journals. Imed is the author/co-author of two books as well as more than 100 patents and scientific papers. His research interest is in the area of Speech Recognition and NLP, including dialog systems, language understanding, user satisfaction and IR.
at Microsoft Advanced Technology Lab in Cairo. He is leading a team working on speaker recognition, Arabic speech recognition and language understanding. He has long research and development experience in speech and natural language processing and their applications. He worked for several companies and research organizations in the United States and Europe and participated in research projects to develop and advance the state-of-the-art of speech and natural language processing systems. He also taught for several years at Cairo University, where he was Associate Professor until 2004. Mohamed received his Ph.D. from Cairo University in 1995. After graduation, he spent long periods at INRIA Lorraine, Nancy, France, the Multimedia research department at Bell Laboratories, BBN Technologies, Cambridge, MA, and IBM Thomas J. Watson Research Center, Yorktown Heights, NY. He participated in projects for developing a speech-to-speech translation prototype, broadcast news and conversational telephone speech transcription systems, automatic call routing for call center applications, optical character recognition system, and automatic speaker and language identification. In June 2008 he joined the newly created Orange Lab as head of voice and multi-media services. He led a team of developers and researchers to come up with innovative products for Orange affiliates in the middle-east and Africa.
at the University of Helwan, Egypt. He is a senior research scientist. Dr. Hifny received his M.Sc. and B.Sc. degrees in electronics and communication engineering in 1995 and 2000 respectively, from the University of Cairo, Egypt. In 2006, he received the PhD degree from the University of Sheffield, U.K. In 2000, he joined Research and Development International (RDI), where he worked on research in text-to-speech (ArabTalk), limited domain speech compression, and speech verification (HAFS) projects. In addition, he was a postdoctoral fellow in the Human Language Technologies Group at IBM T.J. Watson Research Center in 2007.
of speech technology at Edinburgh. He has made significant contributions to speech technology, with over 250 publications in the area (h-index 51), and he and his students have won several best paper awards for their work in speech recognition in the past few years. He has led several large projects in the field, including the EPSRC Programme Grant Natural Speech Technology and the large EU projects SUMMA, AMI, and AMIDA.
of the Arabic Language Technologies (ALT) group at Qatar Computing Research Institute (QCRI), Stephan is responsible for helping to define the overall research agenda of QCRI and of the ALT team in particular.
His research focus is on statistical machine translation (SMT), where statistical models and ML techniques are used to learn from existing (human) translations.
I have been working at IBM's TJ Watson Research Center since 1995. Currently, I manage a team of researchers in the Speech Recognition and Synthesis Research Group and co-ordinate research activities across IBM's world-wide research labs in China, Tokyo, Prague and Haifa. I am also an adjunct professor at Columbia University, where I teach a course on automatic speech recognition along with some of my colleagues at IBM, Michael Picheny and Stanley Chen. I am currently serving my second term on the Speech and Language Technical Committee (SLTC) of the IEEE. I have had the pleasure of closely working with students from several universities and serving on their dissertation committees. I am a senior member of the IEEE, serve on the editorial board of Computers, Speech and Language, and a member of ACL. I am a technical area chair for ICASSP 2013, was the technical area chair for Interspeech 2012, and was one of the lead organizers and technical chair of IEEE ASRU 2011 in Hawaii. I co-organized the HLT-NAACL workshop on language modeling in 2012, special sessions on Sparse Representations in Interspeech 2010 and on Speech Transcription and Machine Translation at the 2007 ICASSP in Honolulu, and organized the HLT-NAACL 2004 Workshop on Interdisciplinary Approaches to Speech Indexing and Retrieval. I review for ICASSP, Inerspeech, NAACL, ACL, and IEEE Transactions and serve on NSF review panels. I have published over 150 papers and been granted over 20 U.S. patents. My research interests include speech recognition and synthesis algorithms, statistical modeling, signal processing, pattern recognition and machine learning. .