Technical Program

Paper Detail

Session:Multilinguality in Speech Processing
Time:Tuesday, May 18, 14:25 - 14:42
Presentation: Special Session Lecture
Topic: Special Sessions: Multilinguality in Speech Processing
Authors: Alex Waibel; Carnegie Mellon University 
 Tanja Schultz; Carnegie Mellon University 
 Stephan Vogel; Carnegie Mellon University 
 Christian Fügen; Karlsruhe University 
 Matthias Honal; Karlsruhe University 
 Muntsin Kolss; Karlsruhe University 
 Jürgen Reichert; Karlsruhe University 
 Sebastian Stüker; Karlsruhe University 
Abstract: In this paper we presented an approach towards the tighter coupling of statically based speech translation that uses multiple layers of reduction and transformation by cascading several stochastic source-channel models. This approach more radically relies on learning techniques to overcome today’s limits of language and domain portable conversational speech translation systems. The disfluency cleaner for English achieved a recall of 77.2% and a precision of 90.2%. The same algorithms and models were effortless adapted to Mandarin Chinese giving 49.4% recall and 76.8% precision. The results on translation suggest that MT systems can be successfully constructed for any language pair by cascading multiple MT systems via English. Moreover, end-to-end performance can be improved, if the interlingua language is enriched with additional linguistic information that can be derived automatically and monolingually in a data-driven fashion.

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