Článek v časopise

HAIN Thomas, BURGET Lukáš, DINES John, GARNER Phillip N., GRÉZL František, EL Hannani Asmaa, HUIJBREGTS Marijn, KARAFIÁT Martin, LINCOLN Mike a WAN Vincent. Transcribing Meetings with the AMIDA System. IEEE Transactions on Audio, Speech, and Language Processing. 2012, roč. 20, č. 2, s. 486-498. ISSN 1558-7916. Dostupné z: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5983475
Jazyk publikace:angličtina
Název publikace:Transcribing Meetings with the AMIDA System
Název (cs):Rozpoznávání meetingů se systémy AMIDA
Strany:486-498
Kniha:IEEE Transactions on Audio, Speech, and Language Processing
Místo vydání:New York, US
Rok:2012
URL:http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5983475
Časopis:IEEE Transactions on Audio, Speech, and Language Processing, roč. 20, č. 2, US
ISSN:1558-7916
DOI:10.1109/TASL.2011.2163395
Vydavatel:IEEE Signal Processing Society
URL:http://www.fit.vutbr.cz/research/groups/speech/publi/2012/hain_IEEE_TOASALP_2012_journal_05983475.pdf [PDF]
Klíčová slova
AMI corpus, Juicer, meeting transcription, multiple distant microphone, resource optimisation, rich text
Anotace
Článek pojednává o systémech AMIDA, které byly vyvinuty pro rozpoznávání přednášek a vystoupení na konferencích a účastnily se RT evaluací pořádaných NIST v letech 2007 a 2009.
Abstrakt
In this paper, we give an overview of the AMIDA systems for transcription of conference and lecture room meetings. The systems were developed for participation in the Rich Transcription evaluations conducted by the National Institute for Standards and Technology in the years 2007 and 2009 and can process close talking and far field microphone recordings. The paper first discusses fundamental properties of meeting data with special focus on the AMI/AMIDA corpora. This is followed by a description and analysis of improved processing and modeling, with focus on techniques specifically addressing meeting transcription issues such as multi-room recordings or domain variability. In 2007 and 2009, two different strategies of systems building were followed. While in 2007 we used our traditional style system design based on cross adaptation, the 2009 systems were constructed semi-automatically, supported by improved decoders and a new method for system representation. Overall these changes gave a 6%-13% relative reduction in word error rate compared to our 2007 results while at the same time requiring less training material and reducing the real-time factor by five times. The meeting transcription systems are available at www.webasr.org.
BibTeX:
@ARTICLE{
   author = {Thomas Hain and Luk{\'{a}}{\v{s}} Burget and John
	Dines and N. Phillip Garner and Franti{\v{s}}ek
	Gr{\'{e}}zl and Asmaa Hannani El and Marijn
	Huijbregts and Martin Karafi{\'{a}}t and Mike
	Lincoln and Vincent Wan},
   title = {Transcribing Meetings with the AMIDA System},
   pages = {486--498},
   booktitle = {IEEE Transactions on Audio, Speech, and Language Processing},
   journal = {IEEE Transactions on Audio, Speech, and Language Processing},
   volume = 20,
 number = 2,
   year = 2012,
   location = {New York, US},
   publisher = {IEEE Signal Processing Society},
   ISSN = {1558-7916},
   doi = {10.1109/TASL.2011.2163395},
   language = {english},
   url = {http://www.fit.vutbr.cz/research/view_pub.php.cs?id=9945}
}

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