Search Results for author: Anton Leuski

Found 14 papers, 0 papers with code

Evaluation of Off-the-shelf Speech Recognizers Across Diverse Dialogue Domains

no code implementations LREC 2020 Kallirroi Georgila, Anton Leuski, Volodymyr Yanov, David Traum

We evaluate several publicly available off-the-shelf (commercial and research) automatic speech recognition (ASR) systems across diverse dialogue domains (in US-English).

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

Which Model Should We Use for a Real-World Conversational Dialogue System? a Cross-Language Relevance Model or a Deep Neural Net?

no code implementations LREC 2020 Seyed Hossein Alavi, Anton Leuski, David Traum

We compare two models for corpus-based selection of dialogue responses: one based on cross-language relevance with a cross-language LSTM model.

SHIHbot: A Facebook chatbot for Sexual Health Information on HIV/AIDS

no code implementations WS 2017 Jacqueline Brixey, Rens Hoegen, Wei Lan, Joshua Rusow, Karan Singla, Xusen Yin, Ron artstein, Anton Leuski

We present the implementation of an autonomous chatbot, SHIHbot, deployed on Facebook, which answers a wide variety of sexual health questions on HIV/AIDS.

Chatbot Retrieval

Lessons in Dialogue System Deployment

no code implementations WS 2017 Anton Leuski, Ron artstein

We analyze deployment of an interactive dialogue system in an environment where deep technical expertise might not be readily available.

An Active Learning Based Approach For Effective Video Annotation And Retrieval

no code implementations27 Apr 2015 Moitreya Chatterjee, Anton Leuski

Conventional multimedia annotation/retrieval systems such as Normalized Continuous Relevance Model (NormCRM) [16] require a fully labeled training data for a good performance.

Active Learning Clustering +1

The BladeMistress Corpus: From Talk to Action in Virtual Worlds

no code implementations LREC 2012 Anton Leuski, Carsten Eickhoff, James Ganis, Victor Lavrenko

Thirdly, a joined analysis of both the language and the actions would empower us to build effective modes of the users and their behavior.

Text Classification

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