Amazon has selected Johns Hopkins University among the first four schools to receive support from the Alexa Fund Fellowship, a new program designed to encourage advances in voice communication between people and machines.
Dept Of Electrical And Computer Engrg
Hackerman Hall 325
3400 N Charles St
The Third Frederick Jelinek Memorial Summer Workshop, organized and hosted by the Johns Hopkins Center for Language and Speech Processing, is under way. The six-week workshop—which marks the 21st summer workshop in CLSP’s history—seeks to advance and promote machine learning for speech language and computer vision technology. Workshop attendees—comprising researchers from academia, government and industry […]
- Ph.D. 1997, University of Maryland, College Park
- Other Bachelor's Degree (B.Tech) 1988, Indian Institute of Technology, Bombay
- 2009 - Present: Lead for Speech Research, JHU Human Language Technology Center of Excellence
- Statistical models of human language;
- Automatic speech recognition;
- Machine translation;
- Natural language processing.
- 2011: My student Markus Dreyer was awarded the AMTA Student Scholarship/Travel Award for a paper of which I am a co-author.
- 2006: My Ph.D student - Arnab Ghoshal - was awarded a Best Student Paper prize at the 2006 IEEE International Conference on Acoustics - Speech and Signal Processing for a paper of which I am a co-author.
- 2003: A paper jointly authored by my PhD student - Woosung Kim - and me was nominated for the Best Paper Award at the 2004 Conference on Empirical Methods in Natural Language Processing - held at Sopporo - Japan - in May 2003.
- 1999: My Ph.D student - Jun Wu - was awarded the ELSNET Best Student Paper prize at EuroSpeech 1999 for a paper of which I am a co-author.
- Jedynak, B., Khudanpur, S., Yazgan, A. Estimation of Probability Mass Functions from Small Samples.
- Ahmidi, N., Gao, Y., Béjar, B., Vedula, S., Khudanpur, S., Vidal, R., Hager, G. (2013). String motif-based description of tool motion for detecting skill and gestures in robotic surgery.. Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. 16(Pt 1). 26-33.
- Reiley, C. E., Lin, H. C., Varadarajan, B., Vagvolgyi, B., Khudanpur, S., Yuh, D., Hager, G. (2008). Automatic recognition of surgical motions using statistical modeling for capturing variability. Studies in health technology and informatics. 132. 396.
- Karakos, D., Khudanpur, S., Marchette, D. J., Papamarcou, A., Priebe, C. (2008). On the minimization of concave information functionals for unsupervised classification via decision trees. Statistics & Probability Letters. 78(8). 975–984.
- Jedynak, B., Khudanpur, S., Yazgan, A. (2005). Estimating Probabilities from Small Samples. 2005 Proceedings of the American Statistical Association, Statistical computing section [CD-ROM], Alexandria, VA: American Statistical Association.
- Jedynak, B., Khudanpur, S. (2005). Maximum likelihood set for estimating a probability mass function. Neural computation. 17(7). 1508–1530.
- Tao, L., Elhamifar, E., Khudanpur, S., Hager, G., Vidal, R. (2012). Sparse hidden markov models for surgical gesture classification and skill evaluation. Information Processing in Computer-Assisted Interventions. Springer Berlin Heidelberg. 167–177.
- Rosti, A., Matusov, E., Smith, J., Ayan, N., Eisner, J., Karakos, D., Khudanpur, S., Leusch, G., Li, Z., Matsoukas, S., Ney, H., Schwartz, R., Zhang, B., Zheng, J. (2011). Confusion Network Decoding for MT System Combination. Handbook of Natural Language Processing and Machine Translation. Springer. 333–361.
- Varadarajan, B., Reiley, C., Lin, H., Khudanpur, S., Hager, G. (2009). Data-derived models for segmentation with application to surgical assessment and training. Medical Image Computing and Computer-Assisted Intervention–MICCAI 2009. Springer Berlin Heidelberg. 426–434.
- Hager, G., Varadarajann, B., Khudanpur, S., Kumar, R., Reiley, C. E., Lin, H. C. (2012). METHOD AND SYSTEM FOR QUANTIFYING TECHNICAL SKILL.
- Hager, G., Reiley, C. E., Varadarajann, B., Khudanpur, S., Lin, H. C., Kumar, R. (2010). METHOD AND SYSTEM FOR QUANTIFYING TECHNICAL SKILL.
- Tao, L., Elhamifar, E., Khudanpur, S., Hager, G., Vidal, R. (2012). Sparse Hidden Markov Models for Surgical Gesture Classification and Skill Evaluation. Information Processing in Computed Assisted Interventions.
- Li, Z., Eisner, J., Wang, Z., Khudanpur, S., Roark, B. (2011). Minimum Imputed Risk: Unsupervised Discriminative Training for Machine Translation. Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP). 920–929.
- Li, Z., Wang, Z., Khudanpur, S., Eisner, J. (2010). Unsupervised Discriminative Language Model Training for Machine Translation using Simulated Confusion Sets. Proceedings of the 23rd International Conference on Computational Linguistics (COLING). 656–664.
- Li, Z., Eisner, J., Khudanpur, S. (2009). Variational Decoding for Statistical Machine Translation. Proceedings of the 47th Annual Meeting of the Association for Computational Linguistics (ACL). 593–601.
- Zhou, H., Karakos, D., Khudanpur, S., Andreou, A., Priebe, C. (2009). On projections of Gaussian distributions using maximum likelihood criteria. Proceedings of the 2009 Information Theory and Applications Workshop (ITAW). 1–5.
- Karakos, D., Eisner, J., Khudanpur, S., Dreyer, M. (2008). Machine Translation System Combination using ITG-based Alignments. Proceedings of ACL-08: HLT, Short Papers. 81–84.
- Karakos, D., Eisner, J., Khudanpur, S., Priebe, C. (2007). Cross-Instance Tuning of Unsupervised Document Clustering Algorithms. Human Language Technologies: Proceedings of the Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT). 252–259.
- Karakos, D., Khudanpur, S., Eisner, J., Priebe, C. (2007). Iterative Denoising Using Jensen-Renyí Divergences with an Application to Unsupervised Document Categorization. Proceedings of the International Conference on Acoustics, Speech and Signal Processing (ICASSP).
- Karakos, D., Khudanpur, S., Eisner, J., Priebe, C. (2005). Unsupervised Classification via Decision Trees: An Information-Theoretic Perspective. Proceedings of the 2005 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 5. 1081–1084.