Extraction and comparison of various prosodic feature sets on sentence segmentation task for Turkish broadcast news data

Göster/ Aç
Tarih
2014-05-14Yazar
Dalva, Doğan
Revidi, İzel D.
Güz, Ümit
Gürkan, Hakan
Metadata
Tüm öğe kaydını gösterÖzet
In this work, prosodic features of the Turkish Broadcast News (BN) data are extracted using an open source prosodic feature extraction tool based on Praat. The profiles and effectiveness of these features are also investigated for the sentence segmentation task on the Turkish BN data. We not only used some combinations of the feature sets but also collected some of them in one prosodic feature model in order to achieve one of the best performance. The results of the experiments show that some combinations of the prosodic feature sets are very useful for the automatic sentence segmentation task on the Turkish BN data.
İlgili öğeler
Başlık, yazar, küratör ve konuya göre gösterilen ilgili öğeler.
-
Extraction and selection of muscle based features for facial expression recognition
Benli, Kristin Surpuhi; Eskil, Mustafa Taner (IEEE Computer Soc, 2014-08-24)In this study we propose a new set of muscle activity based features for facial expression recognition. We extract muscular activities by observing the displacements of facial feature points in an expression video. The ... -
A novel human identification system based on electrocardiogram features
Gürkan, Hakan; Güz, Ümit; Yarman, Bekir Sıddık Binboğa (IEEE, 2013)In this work, we present a novel biometric authentication approach based on combination of AC/DCT features, MFCC features, and QRS beat information of the ECG signals. The proposed approach is tested on a subset of 30 ... -
Anatomy based Features for Facial Expression Recognition
Benli, Kristin Surpuhi; Eskil, Mustafa Taner (IEEE, 2014-04-23)In this study we propose a set of anatomy based features for facial expression recognition. The muscle forces that constitute an expression are solved by tracking carefully selected facial feature points. These points are ...