DocumentCode
152906
Title
Extracting the prosodic information for Turkish broadcast news data and using on the sentence segmentation task
Author
Dalva, Dogan ; Revidi, Izel D. ; Guz, Umit ; Gurkan, Hakan
Author_Institution
Elektrik-Elektron. Muhendisligi Bolumu, Isik Univ., Istanbul, Turkey
fYear
2014
fDate
23-25 April 2014
Firstpage
1810
Lastpage
1813
Abstract
In this study, extracting the prosodic information for Turkish Broadcast News Data using the open source tools and comparing the sentence segmentation performances of these grouped prosodic information on the raw data obtained as an output from the Automatic Speech Recognition System are established. Especially for the sentence segmentation task, a very promising prosodic feature set is obtained.
Keywords
feature extraction; natural language processing; public domain software; speech recognition; Turkish broadcast news data; automatic speech recognition system; open source tools; prosodic feature set; prosodic information extraction; sentence segmentation task; Conferences; Entropy; Hidden Markov models; NIST; Signal processing; Speech; Training data; automatic speech segmentation; prosodic feature set; prosody; sentence segmentation;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing and Communications Applications Conference (SIU), 2014 22nd
Conference_Location
Trabzon
Type
conf
DOI
10.1109/SIU.2014.6830603
Filename
6830603
Link To Document