Preprocessing Techniques for End-To-End Trainable RNN-Based Conversational System

Preprocessing Techniques for End-To-End Trainable RNN-Based Conversational System

Spoken dialogue system interfaces are gaining increasing attention, with examples including Apple’s Siri, Amazon’s Alexa, and numerous other products. Yet most existing solutions remain heavily data-driven, and face limitations in integrating and handling data semantics. They mainly rely on statisti...

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Bibliographic Details
Main Author: Maziad, Hussein (author)
Other Authors: Rammouz, Julie-Ann (author), El Asmar, Boulos (author), Tekli, Joe (author)
Format: conferenceObject
Published: 2021
Subjects:
Software engineering > Congresses
Web services > Congresses
Online Access:http://hdl.handle.net/10725/16286
https://doi.org/10.1007/978-3-030-74296-6_20
http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php
https://link.springer.com/chapter/10.1007/978-3-030-74296-6_20
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http://hdl.handle.net/10725/16286
https://doi.org/10.1007/978-3-030-74296-6_20
http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php
https://link.springer.com/chapter/10.1007/978-3-030-74296-6_20

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