IWSLT.2015

[P] [K] The RWTH Aachen machine translation system for IWSLT 2015

[P] [K] The MITLL-AFRL IWSLT 2015 MT system

[P] [K] The Edinburgh machine translation systems for IWSLT 2015

[P] [K] The MLLP ASR systems for IWSLT 2015

[P] [K] The Heidelberg University English-German translation system for IWSLT 2015

[P] [K] The LIUM ASR and SLT systems for IWSLT 2015

[P] [K] The UMD machine translation systems at IWSLT 2015

[P] [K] The KIT translation systems for IWSLT 2015

[P] [K] The 2015 KIT IWSLT speech-to-text systems for English and German

[P] [K] Stanford neural machine translation systems for spoken language domains

[P] [K] The English-Vietnamese machine translation system for IWSLT 2015

[P] [K] The IOIT English ASR system for IWSLT 2015

[P] [K] The 12R ASR system for IWSLT 2015

[P] [K] The JAIST-UET-MITI machine translation systems for IWSLT 2015

[P] [K] PJAIT systems for the IWSLT 2015 evaluation campaign enhanced by comparable corpora

[P] [K] The NAIST English speech recognition system for IWSLT 2015

[P] [K] Improvement of word alignment models for Vietnamese-to-English translation

[P] [K] Applying cross-entropy difference for selecting parallel training data from publicly available sources for conversational machine translation

[P] [K] Source discriminative word lexicon for translation disambiguation

[P] [K] Phrase-level estimation for machine translation

[P] [K] Improving continuous space language models auxiliary features

[P] [K] Multifeature modular deep neural network acoustic models

[P] [K] Using language adaptive deep neural networks for improved multilingual speech recognition

[P] [K] Punctuation insertion for real-time spoken language translation

[P] [K] Class-based N-gram language difference models for data selection