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» Improving Language Models by Clustering Training Sentences
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IROS
2007
IEEE
94views Robotics» more  IROS 2007»
14 years 2 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
13 years 9 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
EMNLP
2009
13 years 5 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...
EMNLP
2011
12 years 7 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...
ACL
2007
13 years 9 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