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» Improving Language Models by Clustering Training Sentences
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IROS
2007
IEEE
94views Robotics» more  IROS 2007»
15 years 4 months ago
Two-way translation of compound sentences and arm motions by recurrent neural networks
- We present a connectionist model that combines motions and language based on the behavioral experiences of a real robot. Two models of recurrent neural network with parametric bi...
Tetsuya Ogata, Masamitsu Murase, Jun Tani, Kazunor...
EACL
2006
ACL Anthology
14 years 11 months ago
Discriminative Sentence Compression with Soft Syntactic Evidence
We present a model for sentence compression that uses a discriminative largemargin learning framework coupled with a novel feature set defined on compressed bigrams as well as dee...
Ryan T. McDonald
78
Voted
EMNLP
2009
14 years 8 months ago
Discriminative Corpus Weight Estimation for Machine Translation
Current statistical machine translation (SMT) systems are trained on sentencealigned and word-aligned parallel text collected from various sources. Translation model parameters ar...
Spyros Matsoukas, Antti-Veikko I. Rosti, Bing Zhan...
108
Voted
EMNLP
2011
13 years 10 months ago
Training a Parser for Machine Translation Reordering
We propose a simple training regime that can improve the extrinsic performance of a parser, given only a corpus of sentences and a way to automatically evaluate the extrinsic qual...
Jason Katz-Brown, Slav Petrov, Ryan T. McDonald, F...
102
Voted
ACL
2007
14 years 11 months ago
Pivot Language Approach for Phrase-Based Statistical Machine Translation
This paper proposes a novel method for phrase-based statistical machine translation by using pivot language. To conduct translation between languages Lf and Le with a small biling...
Hua Wu, Haifeng Wang