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Towards efficient human machine speech communication: The speech graffiti project
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Volume 2 ,  Issue 1  (February 2005) table of contents
Article No. 2  
Year of Publication: 2005
ISSN:1550-4875
Authors
Stefanie Tomko  Carnegie Mellon University, Pittsburgh, PA
Thomas K. Harris  Carnegie Mellon University, Pittsburgh, PA
Arthur Toth  Carnegie Mellon University, Pittsburgh, PA
James Sanders  Carnegie Mellon University, Pittsburgh, PA
Alexander Rudnicky  Carnegie Mellon University, Pittsburgh, PA
Roni Rosenfeld  Carnegie Mellon University, Pittsburgh, PA
Publisher
ACM  New York, NY, USA
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ABSTRACT

This research investigates the design and performance of the Speech Graffiti interface for spoken interaction with simple machines. Speech Graffiti is a standardized interface designed to address issues inherent in the current state-of-the-art in spoken dialog systems such as high word-error rates and the difficulty of developing natural language systems. This article describes the general characteristics of Speech Graffiti, provides examples of its use, and describes other aspects of the system such as the development toolkit. We also present results from a user study comparing Speech Graffiti with a natural language dialog system. These results show that users rated Speech Graffiti significantly better in several assessment categories. Participants completed approximately the same number of tasks with both systems, and although Speech Graffiti users often took more turns to complete tasks than natural language interface users, they completed tasks in slightly less time.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Stefanie Tomko: colleagues
Thomas K. Harris: colleagues
Arthur Toth: colleagues
James Sanders: colleagues
Alexander Rudnicky: colleagues
Roni Rosenfeld: colleagues