Dr. Joseph Keshet

Dr. Joseph Keshet


Joseph Keshet and Samy Bengio, Eds., Automatic Speech and Speaker Recognition: Large Margin and Kernel Methods, John Wiley & Sons, March 2009


Morgan Sonderegger and Joseph Keshet, Automatic Discriminative Measurement of Voice Onset Time, Journal of the Acoustical Society of America, Vol. 132, Issue 6, pp. 3965−3979, 2012


Joseph Keshet, David Grangier and Samy Bengio, Discriminative Keyword Spotting, Speech Communication, Volume 51, Issue 4, pp. 317-329, April 2009.


Koby Crammer, Ofer Dekel, Joseph Keshet, Shai Shalev-Shwartz and Yoram Singer, Online Passive-Aggressive Algorithms, Journal of Machine Learning Research, 7(Mar):551−585, 2006.


Tamir Hazan, Subhransu Maji, Joseph Keshet, Tommi Jaakkola, On Sampling from the Gibbs distribution with Random Maximum A-Posteriori Perturbations, Neural Information and Processing Systems (NIPS), 2013.

Noam Peled, Moshe Bitan, Joseph Keshet, Sarit Kraus, Predicting Human Strategic Decisions Using Facial Expressions, International Joint Conference on Artificial Intelligence (IJCAI), Beijing, China, 2013.

Rohit Prabhavalkar, Karen Livescu, Eric Fosler-Lussier, Joseph Keshet, Discriminative Articulatory Models for Spoken Term Detection in Low-Resource Conversational Settings, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Vancouver, Canada, 2013.

Hao Tang, Joseph Keshet, and Karen Livescu, Discriminative Pronunciation Modeling: A Large-Margin, Feature-Rich Approach,The 50th Annual Meeting of the Association of Computational Linguistics (ACL), 2012.

David McAllester and Joseph Keshet, Generalization Bounds and Consistency for Latent Structural Probit and Ramp Loss, The 25th Annual Conference on Neural Information Processing Systems (NIPS), 2011 (full oral presentation).

Joseph Keshet, Chih-Chieh Cheng, Mark Stoehr, and David McAllester, Direct Error Rate Minimization of Hidden Markov Models, The 12th Annual Conference of the International Speech Communication Association (Interspeech), Florence, Italy, 2011.

Andrew Cotter, Nathan Srebro, and Joseph Keshet, A GPU-Tailored Approach for Training Kernelized SVMs, The 17th ACM Conference on Knowledge Discovery and Data Mining (KDD), San Diego, CA, 2011.


Joseph Keshet, David McAllester, and Tamir Hazan, PAC-Bayesian Approach for Minimization of Phoneme Error Rate, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Prague, Czech Republic, 2011.

David McAllester, Tamir Hazan and Joseph Keshet, Direct Loss Minimization for Structured Prediction,The 24th Annual Conference on Neural Information Processing Systems (NIPS), 2010.


Machine learning; Speech recognition; Audio, speech and language processing