DocumentCode
2973175
Title
Comparing automatic rich transcription for Portuguese, Spanish and English Broadcast News
Author
Batista, Fernando ; Trancoso, Isabel ; Mamede, Nuno J.
Author_Institution
Spoken Language Syst. Lab., INESC ID Lisboa, Lisbon, Portugal
fYear
2009
fDate
Nov. 13 2009-Dec. 17 2009
Firstpage
540
Lastpage
545
Abstract
This paper describes and evaluates a language independent approach for automatically enriching the speech recognition output with punctuation marks and capitalization information. The two tasks are treated as two classification problems, using a maximum entropy modeling approach, which achieves results within state-of-the-art. The language independence of the approach is attested with experiments conducted on Portuguese, Spanish and English broadcast news corpora. This paper provides the first comparative study between the three languages, concerning these tasks.
Keywords
broadcasting; linguistics; maximum entropy methods; natural language processing; speech recognition; English broadcast news; English language; Portuguese broadcast news; Portuguese language; Spanish broadcast news; Spanish language; automatic rich transcription; capitalization information; language independence; maximum entropy modeling; punctuation mark; speech recognition; Automatic speech recognition; Broadcasting; Ear; Entropy; Hidden Markov models; Model driven engineering; NIST; Natural languages; Speech analysis; Speech recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Automatic Speech Recognition & Understanding, 2009. ASRU 2009. IEEE Workshop on
Conference_Location
Merano
Print_ISBN
978-1-4244-5478-5
Electronic_ISBN
978-1-4244-5479-2
Type
conf
DOI
10.1109/ASRU.2009.5373371
Filename
5373371
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