[PDF] Top 20 Stabilizing Minimum Error Rate Training
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Stabilizing Minimum Error Rate Training
... One possible approach to estimating log-linear weights on features is to dispense with the n-best lists employed by Och’s procedure and, instead, to optimize weights by directly accessing the de- coder. The disadvantage ... See full document
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Modeling Letter to Phoneme Conversion as a Phrase Based Statistical Machine Translation Problem with Minimum Error Rate Training
... The recent work of Jiampojamarn et al (2007) combines both of the above approaches in a very in- teresting manner. It uses an EM like algorithm for aligning the letters and phonemes. The algorithm al- lows many-to-many ... See full document
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Efficient Minimum Error Rate Training and Minimum Bayes Risk Decoding for Translation Hypergraphs and Lattices
... Minimum Error Rate Training (MERT) and Minimum Bayes-Risk (MBR) decod- ing are used in most current state-of-the- art Statistical Machine Translation (SMT) ... See full document
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Distributed Minimum Error Rate Training of SMT using Particle Swarm Optimization
... as minimum error rate training (MERT) can be extremely time-consuming, leading to a slow turn- around rate for SMT research and exper- ... See full document
9
Adaptive Minimum Bit Error Rate Beamforming
... Fig. 7. Learning curves of the stochastic gradient adaptive MBER algorithm of Section IV-B averaged over 20 randomly chosen uniformly distributed initial weight values w(0) . SNR = 10 dB, SIR = SIR = 06 dB, and SIR = SIR ... See full document
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Adaptive minimum bit error rate filtering
... averaged over 30 runs, given SNR ¼ 12 dB and two different initial weight vector conditions. From Fig. 4, it can be seen that this stochastic gradient adaptive MBER algorithm has a reasonable convergence rate. ... See full document
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Adaptive Least Error Rate Algorithm for Neural Network Classifiers
... We propose a stochastic gradient adaptive minimum error rate MER algorithm called the least error rate LER for training neural network classi ers.. INTRODUCTION We study the class of neu[r] ... See full document
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Adaptive near minimum error rate training for neural networks with application to multiuser detection in CDMA communication systems
... MER training algorithm for a class of neural networkclassifiers that includes nonlinear equalizers and multiuser detec- ...MER training can in theory be achieved by only adjusting the classifier parameters ... See full document
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Random Restarts in Minimum Error Rate Training for Statistical Machine Translation
... introduced minimum error rate train- ing (MERT) for optimizing feature weights in sta- tistical machine translation (SMT) models, and demonstrated that it produced higher translation quality scores ... See full document
8
Lattice Based Minimum Error Rate Training Using Weighted Finite State Transducers with Tropical Polynomial Weights
... We now wish to find the hypotheses that define the error surface by performing Steps 5 and 6 of the TGMERT algorithm. These two linear functions de- fine two intervals of γ . The linear functions intersect at γ ≈ ... See full document
10
Regularized Minimum Error Rate Training
... Secondly, it offers a globally optimal line search. Un- fortunately, there are several potential difficulties in scaling MERT to larger numbers of features, due to its non-convex loss function and its lack of reg- ... See full document
12
Parsing-based Machine Translation using an Open Source Toolkit: Joshua for Tamil Language
... Our toolkit is written in Java and implements all the essential algorithms described in Chiang (2007): chart parsing, n gram language model integration, beam and cube pruning, and k-best extraction. The toolkit also ... See full document
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A Systematic Comparison of Training Criteria for Statistical Machine Translation
... A problem that we often face in practice is that the correct translation might not be among the can- didates that our MT system produces. Therefore, (Och and Ney, 2002; Och, 2003) defined the trans- lation candidate with ... See full document
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Locally Training the Log Linear Model for SMT
... translation, minimum error rate training (MERT) is a standard method for tuning a single weight with regard to a given development ...local training method to address these two ... See full document
10
The Geometry of Statistical Machine Translation
... is minimum error rate training (MERT), which is an efficient form of line optimisation adapted to the highly non- linear objective functions used in machine ...the error surface over a ... See full document
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Minimum Sample Risk Methods for Language Modeling
... called minimum sample risk ...discriminative training methods in that instead of searching on an ap- proximated loss function, MSR employs a simple heuristic training algorithm that minimizes the ... See full document
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Joint Decoding with Multiple Translation Models
... Table 2 shows the results of comparing individ- ual decoding and joint decoding on the test set. With conventional max-derivation decoding, the hierarchical phrase-based model achieved a BLEU score of 30.11 on the test ... See full document
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Adaptive Minimum Bit Error Rate Beamforming Assisted Receiver for Wireless Communications
... MMSE decision directed training MBER.. Bit Error Rate.[r] ... See full document
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Smart Beamforming for Wireless Communications: A Novel Minimum Bit Error Rate Approach
... 1e-4 MMSE decision directed training MBER.. MMSE decision directed training MBER.[r] ... See full document
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Minimum Error Rate Training by Sampling the Translation Lattice
... Since its introduction, (Och, 2003) there has been various suggestions for optimizing the MERT cri- terion. Zens et al. (2007) use the MERT criterion to optimize the N-best lists using the Downhill Simplex Algorithm ... See full document
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