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Continuous word and phrase vectors have proven useful in a number of NLP tasks. Here we describe our experience using them as a source of features for the SemEval-2015 task 3, consisting of two community question answering subtasks: Answer Selection for categorizing answers as potential, good, and bad with regards to their corresponding questions; and(More)
—We describe an IC that provides a local speech recognition capability for a variety of electronic devices. We start with a generic speech decoder architecture that is programmable with industry standard WFST and GMM speech models. Algorithm and architectural enhancements are incorporated in order to achieve real-time performance amid system-level(More)
Machine translation between Arabic and He-brew has so far been limited by a lack of parallel corpora, despite the political and cultural importance of this language pair. Previous work relied on manually-crafted grammars or pivoting via English, both of which are unsatisfactory for building a scalable and accurate MT system. In this work, we compare(More)
Discriminating between closely-related language varieties is considered a challenging and important task. This paper describes our submission to the DSL 2016 shared-task, which included two sub-tasks: one on discriminating similar languages and one on identifying Arabic dialects. We developed a character-level neural network for this task. Given a sequence(More)
This paper presents ongoing language understanding experiments conducted as part of a larger effort to create a nutrition dialogue system that automatically extracts food concepts from a user's spoken meal description. We first discuss the technical approaches to understanding, including three methods for incorporating word vector features into conditional(More)
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