This paper describes the University of Edinburgh (UEDIN) ASR systems for the 2014 IWSLT Evaluation. Notable fea-tures of the English system include deep neural network acoustic models in both tandem and hybrid configuration with the use of multi-level adaptive networks, LHUC adapta-tion and Maxout units. The German system includes lightly supervised training and a new method for dictionary gener-ation. Our voice activity detection system now uses a semi-Markov model to incorporate a prior on utterance lengths. There are improvements of up to 30 % relative WER on the tst2013 English test set. 1
