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    1. Mentioned In 20 Articles

    2. Modelling Prominence and Emphasis Improves Unit-Selection Synthesis

      Volker Strom1, Ani Nenkova2 , Robert Clark1 , Yolanda Vazquez-Alvarez1, Jason Brenier2 , Simon King1 , Dan Jurafsky2 1 Centre for Speech Technology Research, University of Edinburgh, Edinburgh, UK 2 Linguistics Department, Stanford University, Stanford, CA Abstract In order to address these questions, we recorded a new unit selection voice using scripts that had a variety of emphatic words (marked for the voice talent with capi
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    3. Discriminative Syntactic Language Modeling for Speech Recognition.

      Discriminative Syntactic Language Modeling for Speech Recognition Michael Collins MIT CSAIL mcollins@csail.mit.edu Brian Roark OGI/OHSU roark@cslu.ogi.edu Murat Saraclar Bogazici University murat.saraclar@boun.edu.tr Abstract We describe a method for discriminative training of a language model that makes use of syntactic features. We follow a reranking approach, where a baseline recogniser is used to produce 1000-best output for each acoustic input, and ...
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      Discourse, Entailment, Machine Translation, NER, Parsing, Segmentation, Semantic, Sentiment, Summarization, WSD