Search tasks, comprising a series of search queries serving a common informational need, have steadily emerged as accurate units for developing the next generation of task-aware web search systems. Most prior research in this area has focused on segmenting chronologically ordered search queries into higher level tasks. A more naturalistic viewpoint would involve treating query logs as convolute...

Recent works in Natural Language Processing (NLP) using neural networks have focused on learning dense word representations to perform classification tasks. When dealing with phrase prediction problems, is is common practice to use special tagging schemes to identify segments boundaries. This allows these tasks to be expressed as common word tagging problems. In this paper, we propose to learn ...

Reading is claimed to be the major source of vocabulary growth in L1, but is it also the main source of L2 vocabulary? This paper surveys some experiments in acquiring L2 vocabulary from reading that report very small vocabulary gains from short and long texts. By comparison, reading supplemented with word-focused tasks yields better results. Similarly, when reading is compared with a word-focu...

In this paper we present the approach and system setup of the joint participation of Fondazione Bruno Kessler and University of Edinburgh in the WMT 2013 Quality Estimation shared-task. Our submissions were focused on tasks whose aim was predicting sentence-level Human-mediated Translation Edit Rate and sentence-level post-editing time (Task 1.1 and 1.3, respectively). We designed features that...

Participants ingested a sugar drink or a sugar-free drink and then engaged in a pair of dichotic listening tasks. Tasks presented category labels then played a series of word pairs, one in the left ear and one in the right. Participants attempted to identify pairs containing a target category member. Target category words were homonyms. For example, arms appeared as a target in the "body parts"...