Paper Info
Title
Detecting and extracting named entities from spontaneous speech in a mixed-initiative spoken dialogue context: How May I Help You?sm,tm
Abstract
The understanding module of a spoken dialogue system must extract, from the speech recognizer output, the kind of request expressed by the caller (the call type) and its parameters (numerical expressions, time expressions or proper-names). Such expressions are called Named Entities and their definitions can be either generic or linked to the dialogue application domain. Detecting and extracting such Named Entities within a mixed-initiative dialogue context like How May I Help You?sm,tm (HMIHY) is the subject of this study. After reviewing standard methods based on hand-written grammars and statistical tagging, we propose a new approach, combining the advantages of both in a 2-step process. We also propose a novel architecture which exploits understanding to improve recognition accuracy: the output of the Automatic Speech Recognition module is now a word lattice and the understanding module is responsible for transcribing the word strings which are useful to the Dialogue Manager. All the methods proposed are trained and evaluated on a corpus comprising utterances from live customer traffic.
Year
DOI
Venue
2004
10.1016/j.specom.2003.07.003
Speech Communication
Keywords
Field
DocType
Speech recognition,Spoken dialogue systems,Spoken language understanding,Named entities
Rule-based machine translation,Transcription (linguistics),Architecture,Expression (mathematics),Computer science,Feature extraction,Speech recognition,Exploit,Information extraction,Artificial intelligence,Application domain,Natural language processing
Journal
Volume
Issue
ISSN
42
2
0167-6393
Citations 
PageRank 
References 
25
1.19
18
Authors
4
Name
Order
Citations
PageRank
Frédéric Béchet139747.77
Allen L. Gorin236959.37
Jeremy H. Wright321729.44
Dilek Hakkani-Tür428217.30