Statistical methods for speech recognition
Statistical methods for speech recognition
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Discriminative training and maximum entropy models for statistical machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
1993 benchmark tests for the ARPA spoken language program
HLT '94 Proceedings of the workshop on Human Language Technology
TransType2: an innovative computer-assisted translation system
ACLdemo '04 Proceedings of the ACL 2004 on Interactive poster and demonstration sessions
Computer Assisted Transcription for Ancient Text Images
ICIAR '07 Proceedings of the 4th international conference on Image Analysis and Recognition
Optimum algorithm to minimize human interactions in sequential Computer Assisted Pattern Recognition
Pattern Recognition Letters
Guest editorial: special issue on structured prediction
Machine Learning
Interactive pattern recognition
MLMI'07 Proceedings of the 4th international conference on Machine learning for multimodal interaction
Multimodal Interactive Pattern Recognition and Applications
Multimodal Interactive Pattern Recognition and Applications
Does the Cost Function Matter in Bayes Decision Rule?
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Interactive structured prediction (ISP) is an emerging framework for structured prediction (SP) where the user and the system collaborate to produce a high quality output. Typically, search algorithms applied to ISP problems have been based on the algorithms for fully-automatic SP systems. However, the decision rule applied should not be considered as optimal since the goal in ISP is to reduce human effort instead of output errors. In this work, we present some insight into the theory of the sequential ISP search problem. First, it is formulated as a decision theory problem from which a general analytical formulation of the optimal decision rule is derived. Then, it is compared with the standard formulation to establish under what conditions the standard algorithm should perform similarly to the optimal decision rule. Finally, a general and practical implementation is given and evaluated against three classical ISP problems: interactive machine translation, interactive handwritten text recognition, and interactive speech recognition.