Ara
Toplam kayıt 31, listelenen: 11-20
Extraction and comparison of various prosodic feature sets on sentence segmentation task for Turkish broadcast news data
(IEEE, 2014)
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 ...
A novel human identification system based on electrocardiogram features
(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 ...
A novel biometric authentication approach using electrocardiogram signals
(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 ...
A novel method to represent ECG signals via predefined personalized signature and envelope functions
(IEEE, 2001)
In this paper, a new method to model ECG signals by means of "Predefined Personalized Signature and Envelope Functions" is presented. ECG signals are somewhat unique to a person. Moreover, it presents quasi-stationary ...
Bürünsel, sözcüksel ve biçimbilgisel bilgiyi kullanan co-training ile Türkçe konuşma dilinin otomatik cümle bölütlemesi
(Tübitak, 2015-04)
Co-training, web sayfası sınıflandırması, kelime anlam açıklaştırma ve adlandırılmış varlık tanıma gibi pek çok sınıflandırma işlevinde başarı ile kullanılan oldukça etkili bir makine öğrenme algoritmasıdır. Co-training, ...
Biometric identification using fingertip electrocardiogram signals
(Springer London Ltd, 2018-07)
In this research work, we present a newly fingertip electrocardiogram (ECG) data acquisition device capable of recording the lead-1 ECG signal through the right- and left-hand thumb fingers. The proposed device is ...
EEG signal compression based on classified signature and envelope vector sets
(IEEE Computer Society, 2007)
In this paper, a novel method to compress ElectroEncephaloGram (EEG) Signal is proposed. The proposed method is based on the generation Classified Signature and Envelope Vector Sets (CSEVS) by using an effective k-means ...
A new algorithm for high speed speech and audio coding
(IEEE, 2007)
In this work, a new mathematical modeling approach is proposed for the representation of the speech and audio signals. This approach is based on the generation of the so called Predefined Signature Sequence (PSS) and ...
Effective semi-supervised learning strategies for automatic sentence segmentation
(Elsevier Science BV, 2018-04-01)
The primary objective of sentence segmentation process is to determine the sentence boundaries of a stream of words output by the automatic speech recognizers. Statistical methods developed for sentence segmentation requires ...
A New speech coding algorithm using zero cross and phoneme based SYMPES
(IEEE, 2013-07-11)
In this work, a new low bit rate hybrid speech coding approach which combines the benefits of the SYMPES (Systematic Procedure for Predefined Envelope and Signature Sequences) and zero cross and phoneme based segmentation ...