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  • NL Seminar-T1. Constraints for Transfer Learning for Machine Translation T2.SAY YES AND: BUILDING A SPECIALIZED CORPUS FOR DIGITAL IMPROVISED COMEDY

    Fri, Aug 17, 2018 @ 03:00 PM - 04:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars

    Speaker: Mozhdeh Gheini, Xinyu Wang , USC/ISI

    Talk Title: T1. Constraints for Transfer Learning for Machine Translation T2.SAY YES-AND: BUILDING A SPECIALIZED CORPUS FOR DIGITAL IMPROVISED COMEDY

    Series: Natural Language Seminar

    Abstract: T1.Can we detect the parts responsible for a generic behavior in a model to transfer it to another? In this talk, we first see why this might be a good idea, especially for low resource machine translation. Then we focus on our approach to isolating a behavior. In our case, we specifically focus on coverage during machine translation. We present our results across different languages that show how neural models try to ensure coverage.

    T2. In improvised comedy, saying yes, and.. is a rule of thumb that suggests that one person should accept the other person's offer yes, and then add related information on top of that and. Collecting a yes, and.. corpus is not only helpful for building an improv agent, but can also be used for building conversational skill training tool, improving a dialogue system, etc. I will discuss the methods we have used for building such a dataset, data we have got so far and future considerations.

    Biography: Mozhdeh Gheini is a last semester Computer Science master's student at USC Viterbi School of Engineering. At ISI, she works on improving neural low-resource machine translation under the supervision of Jonathan May. She will be applying for Ph.D. programs this Fall.

    Xinyu is a 2018 summer intern working with Dr. Jonathan May and Dr. Nanyun Peng on computerized improvised comedy. She will be joinging the Language Technologies Institute at Carnegie Mellon University in 2018 fall.

    Host: Nanyun Peng

    More Info: http://nlg.isi.edu/nl-seminar/

    Location: Information Science Institute (ISI) - 11th Flr Conf Rm # 1135, Marina Del Rey

    Audiences: Everyone Is Invited

    Posted By: Peter Zamar


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