Decoding

Statistical machine translation, as well as other areas of human language processing, have recently pushed toward the use of large scale n-gram language models. This paper presents efficient algorithmic and …...

While domain adaptation techniques for SMT have proven to be effective at im- proving translation quality, their practical- ity for a multi-domain environment is of- ten limited because of the …...

AbstractMachine translation (MT) draws from several different disciplines, making it a complex subject to teach. There are excellent pedagogical texts, but problems in MT and current algorithms for solving them …...

Speed of access is a very important prop- erty for phrase tables in phrase based sta- tistical machine translation as they are queried many times per sentence. In this paper …...

This paper describes the statistical machine translation system developed at RWTH Aachen University for the English→German and German→English translation tasks of the EMNLP 2017 Second Conference on Machine Transla- tion …...

AbstractThere have been significant efforts to interpret the encoder of Transformer-based encoder-decoder architectures for neural machine translation (NMT); meanwhile, the decoder remains largely unexamined despite its critical role. During translation, …...

AbstractThis work describes the participation of the MLLP-VRAIN research group in the two shared tasks of the IWSLT 2022 conference: Simultaneous Speech Translation and Speech-to-Speech Translation. We present our streaming-ready …...

AbstractThere are many proposals to reduce constituency parsing to tagging. To figure out what these approaches have in common, we offer a unifying pipeline, which consists of three steps: linearization, …...