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Events for July 10, 2013
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Meet USC: Admission Presentation, Campus Tour, & Engineering TalkWed, Jul 10, 2013
Viterbi School of Engineering Undergraduate Admission
Receptions & Special Events
This half day program is designed for prospective freshmen and family members. Meet USC includes an information session on the University and the Admission process; a student led walking tour of campus and a meeting with us in the Viterbi School. Meet USC is designed to answer all of your questions about USC, the application process and financial aid. Reservations are required for Meet USC. This program occurs twice, once at 8:30 a.m. and again at 12:30 p.m. Please visit https://esdweb.esd.usc.edu/unresrsvp/MeetUSC.aspx to check availability and make an appointment. Be sure to list an Engineering major as your "intended major" on the webform!
Location: Ronald Tutor Campus Center (TCC) - USC Admission Office
Audiences: Everyone Is Invited
Contact: Viterbi Admission
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NL Seminar- Victor Chahuneau: " Translating into Morphologically Rich Languages with Synthetic Phrases"
Wed, Jul 10, 2013 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Victor Chahuneau, CMU
Talk Title: "Translating into Morphologically Rich Languages with Synthetic Phrases"
Series: Natural Language Seminar
Abstract: Translation into morphologically rich languages is an important but recalcitrant problem in machine translation. When confronted with the large vocabulary sizes resulting from various morphological phenomena, the independence assumptions made by standard translation models mean that vast amounts of parallel training data (which do not generally exist) would be necessary to reliably estimate the numerous required parameters. On the other hand, previous attempts to remedy this situation have been unsatisfying either because they were highly language-dependent, or because they failed from a modeling perspective (e.g., they improved performance on long-tail types at the expense of frequent types).
We present a simple and effective approach that deals with the problem in two phases. First, a discriminative model is learned to predict inflections of target words from rich source-side annotations. Then, this model is used to create additional sentence-specific phrases that are added to a standard translation model prior to decoding. Our approach relies on morphological analysis of the target language but we show that an unsupervised Bayesian model can also be used in place of a standard supervised analyzer. We report significant improvements in translation quality when translating from English to Russian, Hebrew and Swahili.
Biography: http://victor.chahuneau.fr/
Host: Qing Dou
More Info: http://nlg.isi.edu/nl-seminar/
Location: Information Science Institute (ISI) - Conf Rm # 689, Marina Del Rey
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: http://nlg.isi.edu/nl-seminar/
