Skip to main content
Proceedings of the National Academy of Sciences of the United States of America logoLink to Proceedings of the National Academy of Sciences of the United States of America
. 1995 Oct 24;92(22):10017–10022. doi: 10.1073/pnas.92.22.10017

Deployment of human-machine dialogue systems.

D B Roe 1
PMCID: PMC40728  PMID: 7479719

Abstract

The deployment of systems for human-to-machine communication by voice requires overcoming a variety of obstacles that affect the speech-processing technologies. Problems encountered in the field might include variation in speaking style, acoustic noise, ambiguity of language, or confusion on the part of the speaker. The diversity of these practical problems encountered in the "real world" leads to the perceived gap between laboratory and "real-world" performance. To answer the question "What applications can speech technology support today?" the concept of the "degree of difficulty" of an application is introduced. The degree of difficulty depends not only on the demands placed on the speech recognition and speech synthesis technologies but also on the expectations of the user of the system. Experience has shown that deployment of effective speech communication systems requires an iterative process. This paper discusses general deployment principles, which are illustrated by several examples of human-machine communication systems.

Full text

PDF
10017

Images in this article

Selected References

These references are in PubMed. This may not be the complete list of references from this article.

  1. Allen J. Linguistic aspects of speech synthesis. Proc Natl Acad Sci U S A. 1995 Oct 24;92(22):9946–9952. doi: 10.1073/pnas.92.22.9946. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Atal B. S. Speech technology in 2001: new research directions. Proc Natl Acad Sci U S A. 1995 Oct 24;92(22):10046–10051. doi: 10.1073/pnas.92.22.10046. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Bates M. Models of natural language understanding. Proc Natl Acad Sci U S A. 1995 Oct 24;92(22):9977–9982. doi: 10.1073/pnas.92.22.9977. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Carlson R. Models of speech synthesis. Proc Natl Acad Sci U S A. 1995 Oct 24;92(22):9932–9937. doi: 10.1073/pnas.92.22.9932. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Kamm C. User interfaces for voice applications. Proc Natl Acad Sci U S A. 1995 Oct 24;92(22):10031–10037. doi: 10.1073/pnas.92.22.10031. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Makhoul J., Schwartz R. State of the art in continuous speech recognition. Proc Natl Acad Sci U S A. 1995 Oct 24;92(22):9956–9963. doi: 10.1073/pnas.92.22.9956. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Marcus M. New trends in natural language processing: statistical natural language processing. Proc Natl Acad Sci U S A. 1995 Oct 24;92(22):10052–10059. doi: 10.1073/pnas.92.22.10052. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Moore R. C. Integration of speech with natural language understanding. Proc Natl Acad Sci U S A. 1995 Oct 24;92(22):9983–9988. doi: 10.1073/pnas.92.22.9983. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Nakatsu R., Suzuki Y. What does voice-processing technology support today? Proc Natl Acad Sci U S A. 1995 Oct 24;92(22):10023–10030. doi: 10.1073/pnas.92.22.10023. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Wilpon J. G. Voice-processing technologies--their application in telecommunications. Proc Natl Acad Sci U S A. 1995 Oct 24;92(22):9991–9998. doi: 10.1073/pnas.92.22.9991. [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from Proceedings of the National Academy of Sciences of the United States of America are provided here courtesy of National Academy of Sciences

RESOURCES