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Robustness in Automatic Speech Recognition

Fundamentals and Applications

  • Book
  • © 1996

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Part of the book series: The Springer International Series in Engineering and Computer Science (SECS, volume 341)

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About this book

Foreword Looking back the past 30 years. we have seen steady progress made in the area of speech science and technology. I still remember the excitement in the late seventies when Texas Instruments came up with a toy named "Speak-and-Spell" which was based on a VLSI chip containing the state-of-the-art linear prediction synthesizer. This caused a speech technology fever among the electronics industry. Particularly. applications of automatic speech recognition were rigorously attempt­ ed by many companies. some of which were start-ups founded just for this purpose. Unfortunately. it did not take long before they realized that automatic speech rec­ ognition technology was not mature enough to satisfy the need of customers. The fever gradually faded away. In the meantime. constant efforts have been made by many researchers and engi­ neers to improve the automatic speech recognition technology. Hardware capabilities have advanced impressively since that time. In the past few years. we have been witnessing and experiencing the advent of the "Information Revolution." What might be called the second surge of interest to com­ mercialize speech technology as a natural interface for man-machine communication began in much better shape than the first one. With computers much more powerful and faster. many applications look realistic this time. However. there are still tremendous practical issues to be overcome in order for speech to be truly the most natural interface between humans and machines.

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Table of contents (13 chapters)

  1. Speech Communication by Humans and Machines

  2. Robustness in ASR: Problems and Issues

  3. Possible Solutions and Some Perspectives

Authors and Affiliations

  • Speech Technology Laboratory, USA

    Jean-Claude Junqua

  • CRIN - INRIA, France

    Jean-Paul Haton

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