Yazar "Akdeniz, Rafet" seçeneğine göre listele

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    Generation of optimum signature base sequences for speech signals
    (IEEE, 2000) Yarman, Bekir Sıddık Binboğa; Akdeniz, Rafet
    In 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.
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    A novel method to represent speech signals
    (Elsevier Science BV, 2005-01) Akdeniz, Rafet; Yarman, Bekir Sıddık Binboğa
    In this work, speech signals are modeled by means of the so-called pre-defined "signature functions". The pre-defined signature functions are generated using the statistical properties of the speech signals. It has been exhibited that, with a few basic signature functions, any speech signal can be generated within a tolerable error.
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    Representation of speech signals by single signature base function within optimum frame length
    (IEEE, 2000) Akdeniz, Rafet; Yarman, Bekir Sıddık Binboğa
    Before 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.