Spoken Language Understanding (PDF)
Systems for Extracting Semantic Information from Speech
(Sprache: Englisch)
Spoken language understanding (SLU) is an emerging field in between
speech and language processing, investigating human/ machine and
human/ human communication by leveraging technologies from signal
processing, pattern recognition, machine learning and...
speech and language processing, investigating human/ machine and
human/ human communication by leveraging technologies from signal
processing, pattern recognition, machine learning and...
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Spoken language understanding (SLU) is an emerging field in between
speech and language processing, investigating human/ machine and
human/ human communication by leveraging technologies from signal
processing, pattern recognition, machine learning and artificial
intelligence. SLU systems are designed to extract the meaning from
speech utterances and its applications are vast, from voice search
in mobile devices to meeting summarization, attracting interest
from both commercial and academic sectors.
Both human/machine and human/human communications can benefit
from the application of SLU, using differing tasks and approaches
to better understand and utilize such communications. This book
covers the state-of-the-art approaches for the most popular SLU
tasks with chapters written by well-known researchers in the
respective fields. Key features include:
* Presents a fully integrated view of the two distinct
disciplines of speech processing and language processing for SLU
tasks.
* Defines what is possible today for SLU as an enabling
technology for enterprise (e.g., customer care centers or company
meetings), and consumer (e.g., entertainment, mobile, car, robot,
or smart environments) applications and outlines the key research
areas.
* Provides a unique source of distilled information on methods
for computer modeling of semantic information in human/machine and
human/human conversations.
This book can be successfully used for graduate courses in
electronics engineering, computer science or computational
linguistics. Moreover, technologists interested in processing
spoken communications will find it a useful source of collated
information of the topic drawn from the two distinct disciplines of
speech processing and language processing under the new area of
SLU.
speech and language processing, investigating human/ machine and
human/ human communication by leveraging technologies from signal
processing, pattern recognition, machine learning and artificial
intelligence. SLU systems are designed to extract the meaning from
speech utterances and its applications are vast, from voice search
in mobile devices to meeting summarization, attracting interest
from both commercial and academic sectors.
Both human/machine and human/human communications can benefit
from the application of SLU, using differing tasks and approaches
to better understand and utilize such communications. This book
covers the state-of-the-art approaches for the most popular SLU
tasks with chapters written by well-known researchers in the
respective fields. Key features include:
* Presents a fully integrated view of the two distinct
disciplines of speech processing and language processing for SLU
tasks.
* Defines what is possible today for SLU as an enabling
technology for enterprise (e.g., customer care centers or company
meetings), and consumer (e.g., entertainment, mobile, car, robot,
or smart environments) applications and outlines the key research
areas.
* Provides a unique source of distilled information on methods
for computer modeling of semantic information in human/machine and
human/human conversations.
This book can be successfully used for graduate courses in
electronics engineering, computer science or computational
linguistics. Moreover, technologists interested in processing
spoken communications will find it a useful source of collated
information of the topic drawn from the two distinct disciplines of
speech processing and language processing under the new area of
SLU.
Autoren-Porträt von Gokhan Tur, Renato De Mori
Gokhan Tur, Microsoft Research, California, USADr Tur is currently a Principal Scientist in the Speech at Microsoft Department at Microsoft Research, Mountain View, California, USA. He was formerly a Research Scientist at SRI International which is an independent, nonprofit research institute conducting client-sponsored research and development for government agencies, commercial businesses, foundations, and other organizations. He has co-authored more than 70 journal and conference papers. Dr. Tur was the recipient of the Speech Communication Journal Best Paper awards by ISCA for 2004-2006 and by EURASIP for 2005-2006. He is a senior member of IEEE, ACL, and ISCA, and a member of IEEE Signal Processing Society (SPS), and Speech and Language Technical Committee (SLTC) for 2006-2008. He was a guest editor of Speech Communication (Elsevier) for a special issue on Spoken Language Understanding (SLU). He has been involved with organising various conferences and is the spoken language processing area chair for ICASSP 2009.
Renato De Mori, University of Avignon, France
Dr De Mori is a Professor of Computer Science at the Université d'Avignon, as well as Director of its Laboratoire d'Informatique and is a Visiting Professor at McGill University, Canada. He is a Fellow of the Computer Society of the IEEE and a Distinguished Lecturer of the IEEE Signal Processing Society. He is the author or editor of four books and has published more than 100 scientific papers in many international journals. Professor De Mori has been a member of the Executive Advisory Board at the IBM Toronto Lab, Scientific Advisor at France Télécom R&D, Chairman of the Computer and Information Systems Committee, Natural Sciences and Engineering Council of Canada, Vice-President R&D, Centre de Recherche en Informatique de Montréal.
Bibliographische Angaben
- Autoren: Gokhan Tur , Renato De Mori
- 2011, 1. Auflage, 480 Seiten, Englisch
- Verlag: John Wiley & Sons
- ISBN-10: 1119992702
- ISBN-13: 9781119992707
- Erscheinungsdatum: 10.03.2011
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