Entry Lamel:2009:AST from talip.bib

Last update: Sun Oct 15 02:55:04 MDT 2017                Valid HTML 3.2!

Index sections

Top | Symbols | Numbers | Math | A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z

BibTeX entry

@Article{Lamel:2009:AST,
  author =       "Lori Lamel and Abdelkhalek Messaoudi and Jean-Luc
                 Gauvain",
  title =        "Automatic Speech-to-Text Transcription in {Arabic}",
  journal =      j-TALIP,
  volume =       "8",
  number =       "4",
  pages =        "18:1--18:??",
  month =        dec,
  year =         "2009",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1644879.1644885",
  ISSN =         "1530-0226 (print), 1558-3430 (electronic)",
  ISSN-L =       "1530-0226",
  bibdate =      "Mon Mar 29 15:37:17 MDT 2010",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/talip.bib",
  abstract =     "The Arabic language presents a number of challenges
                 for speech recognition, arising in part from the
                 significant differences in the spoken and written
                 forms, in particular the conventional form of texts
                 being non-vowelized. Being a highly inflected language,
                 the Arabic language has a very large lexical variety
                 and typically with several possible (generally
                 semantically linked) vowelizations for each written
                 form. This article summarizes research carried out over
                 the last few years on speech-to-text transcription of
                 broadcast data in Arabic. The initial research was
                 oriented toward processing of broadcast news data in
                 Modern Standard Arabic, and has since been extended to
                 address a larger variety of broadcast data, which as a
                 consequence results in the need to also be able to
                 handle dialectal speech. While standard techniques in
                 speech recognition have been shown to apply well to the
                 Arabic language, taking into account language
                 specificities help to significantly improve system
                 performance.",
  acknowledgement = ack-nhfb,
  articleno =    "18",
  fjournal =     "ACM Transactions on Asian Language Information
                 Processing",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?&idx=J820",
  keywords =     "Arabic language processing; automatic speech
                 recognition; mophological decomposition; speech
                 processing; speech-to-text transcription",
}

Related entries