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Yayın Generation of optimum signature base sequences for speech signals(IEEE, 2000) Yarman, Bekir Sıddık Binboğa; Akdeniz, RafetIn our previous publications [1-6], we proposed a novel method to represent signals in terms of, so called, "Signature Base Functions-SBF' which were extracted from the physical features of the waveform under consideration. In [1-6], SBF were determined in ad-hoc manner, which requires tedious search process, and they were not orthogonal. Furthermore, optimality of SBF was in question. In this work however, we suggest a well-organised procedure to generate "Optimum Orthogonal Signature Base Functions-OSBF' for selected waveforms, which in turn provides excellent means for signal representations. II is shown that the new method of signal representation, which is based on OSBF, requires less computation time with substantial signal compression and results in efficient speaker dependent recognition.Yayın Representation of speech signals by single signature base function within optimum frame length(IEEE, 2000) Akdeniz, Rafet; Yarman, Bekir Sıddık BinboğaBefore this study, we proposed a novel method to represent signals in terms of, so called, “Signature Base Functions-SBF" which were extracted from the physical features of the waveform under consideration. SBF were determined in ad-hoc manner, which requires tedious search process, and they were not orthogonal. Furthermore, optimality of SBF was in question. In this work however, we suggest a well-organized procedure to generate “Optimum Orthogonal Signature Base Functions-OSBF" for selected waveforms, which in turn provides excellent means for signal representations. It is shown that the new method of signal representation, which is based on OSBF, requires less computation time with substantial signal compression and results in efficient speaker dependent recognition.Yayın Extension of conventional co-training learning strategies to three-view and committee-based learning strategies for effective automatic sentence segmentation(IEEE, 2018) Dalva, Doğan; Güz, Ümit; Gürkan, HakanThe objective of this work is to develop effective multi-view semi-supervised machine learning strategies for sentence boundary classification problem when only small sets of sentence boundary labeled data are available. We propose three-view and committee-based learning strategies incorporating with co-training algorithms with agreement, disagreement, and self-combined learning strategies using prosodic, lexical and morphological information. We compare experimental results of proposed three-view and committee-based learning strategies to other semi-supervised learning strategies in the literature namely, self-training and co-training with agreement, disagreement, and self-combined strategies. The experiment results show that sentence segmentation performance can be highly improved using multi-view learning strategies that we propose since data sets can be represented by three redundantly sufficient and disjoint feature sets. We show that the proposed strategies substantially improve the average performance when only a small set of manually labeled data is available for Turkish and English spoken languages, respectively.Yayın Fast inter-mode decision and selective quarter-pel refinement in H.264 video coding(IEEE, 2008) Ateş, Hasan FehmiIn H.264 video coding standard, there exist several inter - prediction modes that use macroblock partitions with variable block sizes. Choosing a rate-distortion optimal coding mode for each macroblock is essential for the best possible coding performance, but also prohibitive due to the heavy computational complexity associated with the required rate-distortion calculations. Likewise, sub-pel motion refinement improves the coding efficiency, but becomes a major computational bottleneck when integer-pel search is executed fast. In this paper, we present a simple strategy to reduce the complexity of quarter-pel refinement and inter-mode decision with minimum loss of coding efficiency. Based on the results of the half-pel motion estimation step, our method evaluates the likelihood of each inter-coding mode being optimal. Then, quarter-pel refinement and actual rate and distortion are computed for only those coding modes with sufficient chance of being optimal. We claim that this method minimizes optimal mode estimation error at a given level of refinement and mode decision complexity. Simulation results show that the algorithm speeds up quarter-pel search and inter-mode selection modules by a factor of about 6 with less than 0.12 dB PSNR loss.Yayın EEG signal compression based on classified signature and envelope vector sets(IEEE Computer Society, 2007) Gürkan, Hakan; Güz, Ümit; Yarman, Bekir Sıddık BinboğaIn 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 clustering algorithm. In this work on a frame basis, any EEG signal is modeled by multiplying three parameters as called the Classified Signature Vector, Classified Envelope Vector, and Frame-Scaling Coefficient. In this case, EEG signal for each frame is described in terms of the two indices R and K of CSEVS and the frame-scaling coefficient. The proposed method is assessed through the use of root-mean-square error (RMSE) and visual inspection measures. The proposed method achieves good compression ratios with low level reconstruction error while preserving diagnostic information in the reconstructed EEG signal.Yayın Türkçe haber yayını verileri için bürünsel bilginin çıkarılması ve cümle bölütlemede kullanılması(IEEE, 2014-04-23) Dalva, Doğan; Revidi, İzel D.; Güz, Ümit; Gürkan, HakanBu çalışmada, Türkçe haber yayını verilerine ilişkin bürünsel özelliklerin açık kaynak kodlu yazılımlar ile çıkarılması ve bürünsel özellik gruplarının Otomatik Konuşma Tanıma (Automatic Speech Recognition) Sistemi çıkışından elde edilen metin üzerinde cümle bölütlemedeki başarımlarının karşılaştırılması gerçekleştirilmiştir.Özellikle cümle bölütleme işlevi için oldukça yüksek başarım oranına sahip bir bürünsel özellik seti elde edilmiştir.Yayın A multilayer annotated corpus for Turkish(IEEE, 2018-06-06) Yıldız, Olcay Taner; Ak, Koray; Ercan, Gökhan; Topsakal, Ozan; Asmazoğlu, CengizIn this paper, we present the first multilayer annotated corpus for Turkish, which is a low-resourced agglutinative language. Our dataset consists of 9,600 sentences translated from the Penn Treebank Corpus. Annotated layers contain syntactic and semantic information including morphological disambiguation of words, named entity annotation, shallow parse, sense annotation, and semantic role label annotation.
