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» Characterizing and Predicting Corrections in Spoken Dialogue...
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ACL
2009
13 years 5 months ago
Predicting Barge-in Utterance Errors by using Implicitly-Supervised ASR Accuracy and Barge-in Rate per User
Modeling of individual users is a promising way of improving the performance of spoken dialogue systems deployed for the general public and utilized repeatedly. We define "im...
Kazunori Komatani, Alexander I. Rudnicky
ACL
2006
13 years 8 months ago
Learning to Say It Well: Reranking Realizations by Predicted Synthesis Quality
This paper presents a method for adapting a language generator to the strengths and weaknesses of a synthetic voice, thereby improving the naturalness of synthetic speech in a spo...
Crystal Nakatsu, Michael White
SIGDIAL
2010
13 years 5 months ago
Advances in the Witchcraft Workbench Project
The Workbench for Intelligent exploraTion of Human ComputeR conversaTions is a new platform-independent open-source workbench designed for the analysis, mining and management of l...
Alexander Schmitt, Wolfgang Minker, Nada Sharaf
ICSE
1997
IEEE-ACM
13 years 11 months ago
Characterizing and Modeling the Cost of Rework in a Library of Reusable Software Components
1 In this paper we characterize and model the cost of rework in a Component Factory (CF) organization. A CF is responsible for developing and packaging reusable software components...
Victor R. Basili, Steven E. Condon, Khaled El Emam...
ACL
1997
13 years 8 months ago
Contrastive Accent in a Data-to-Speech System
Being able to predict the placement of contrastive accent is essential for the assignment of correct accentuation patterns in spoken language generation. I discuss two approaches ...
Mariët Theune