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» Learning User Intentions in Spoken Dialogue Systems
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IJCAI
2007
15 years 1 months ago
A Hybrid Ontology Directed Feedback Selection Algorithm for Supporting Creative Problem Solving Dialogues
We evaluate a new hybrid language processing approach designed for interactive applications that maintain an interaction with users over multiple turns. Specifically, we describe ...
Hao-Chuan Wang, Rohit Kumar, Carolyn Penstein Ros&...
WEBDB
2010
Springer
155views Database» more  WEBDB 2010»
15 years 5 months ago
Learning Topical Transition Probabilities in Click Through Data with Regression Models
The transition of search engine users’ intents has been studied for a long time. The knowledge of intent transition, once discovered, can yield a better understanding of how diď...
Xiao Zhang, Prasenjit Mitra
LREC
2008
101views Education» more  LREC 2008»
15 years 1 months ago
The QALL-ME Benchmark: a Multilingual Resource of Annotated Spoken Requests for Question Answering
This paper presents the QALL-ME benchmark, a multilingual resource of annotated spoken requests in the tourism domain, freely available for research purposes. The languages curren...
Elena Cabrio, Milen Kouylekov, Bernardo Magnini, M...
NLDB
2004
Springer
15 years 5 months ago
Accessing an Information System by Chatting
Abstract. In this paper, we describe a new way to access information by “chatting” to an information source. This involves a chatbot, a program that emulates human conversation...
Bayan Abu Shawar, Eric Atwell
97
Voted
ANLP
2000
109views more  ANLP 2000»
15 years 1 months ago
Predicting Automatic Speech Recognition Performance Using Prosodic Cues
In spoken dialogue systems, it is important for a system to know how likely a speech recognition hypothesis is to be correct, so it can reprompt for fresh input, or, in cases wher...
Diane J. Litman, Julia Hirschberg, Marc Swerts