Paper ID
(Link to PDF)

Title

Author(s)

W96-0204

Modeling Conversational Speech for Speech Recognition

Marie Meteer; Rukmini Iyer

P92-1008

INTEGRATING MULTIPLE KNOWLEDGE SOURCES FOR DETECTION AND CORRECTION OF REPAIRS IN HUMAN-COMPUTER DIALOG

John Bear; John Dowding; Elizabeth Shribergf

C73-2012

AUTOMATIC PATTERN RECOGNITION APPLIED TO SEMANTIC PROBLEMS

R. G. PIOTROWSKI; I. V. PALIBINA

H94-1034

Tagging Speech Repairs

Peter A. Heeman; James Allen

P97-1033

Intonational Boundaries, Speech Repairs, and Discourse Markers: Modeling Spoken Dialog

Peter A. Heeman; James F. Allen

W02-1035

Extracting Clauses for Spoken Language Understanding in Conversational Systems

Narendra Gupta; Srinivas Bangalore

N03-3007

Word Fragments Identification Using Acoustic-Prosodic Features in Conversational Speech

Yang Liu

H05-2011

DialogueView: an Annotation Tool for Dialogue

Fan Yang; Peter A. Heeman

C00-2169

Processing Self Corrections in a speech to speech system

Jorg Spilker; Martin Klarner; Gunther Gorz

W05-1519

Exploring Features for Identifying Edited Regions in Disfluent Sentences

Qi Zhang; Fuliang Weng

A97-1003

High Performance Segmentation of Spontaneous Speech Using Part of Speech and Trigger Word Information

Marsal Gavalda; Klaus Zechner; Gregory Aist

P99-1074

Robust, Finite-State Parsing for Spoken Language Understanding

Edward C. Kaiser

30_pdf_2-col

A TAG-based noisy-channel model of speech repairs

Mark Johnson and Eugene Charniak

P94-1041

Detecting and Correcting Speech Repairs

Peter Heeman; James Allen

100_Paper

Detecting Structural Metadata with Decision Trees and Transformation-Based Learning

Joungbum Kim, Sarah E Schwarm and Mari Ostendorf