Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği

Permanent URI for this collectionhttps://hdl.handle.net/11147/11

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Access type: Open accessAuthor: search.filters.author.Holzapfel, Andre

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  • Article
    Citation - WoS: 4
    Ramcess 2.x Framework-Expressive Voice Analysis for Realtime and Accurate Synthesis of Singing
    (Springer Verlag, 2008) d'Alessandro, Nicolas; Babacan, Onur; Bozkurt, Barış; Dubuisson, Thomas; Holzapfel, Andre; Kessous, Loic; Vlieghe, Maxime
    In this paper we present the work that has been achieved in the context of the second version of the RAMCESS singing synthesis framework. The main improvement of this study is the integration of new algorithms for expressive voice analysis, especially the separation of the glottal source and the vocal tract. Realtime synthesis modules have also been refined. These elements have been integrated in an existing digital instrument: the HANDSKETCH 1.X, a bimanual controller. Moreover this digital instrument is compared to existing systems.
  • Article
    Citation - WoS: 32
    Citation - Scopus: 61
    Three Dimensions of Pitched Instrument Onset Detection
    (Institute of Electrical and Electronics Engineers Inc., 2010) Holzapfel, Andre; Bozkurt, Barış; Stylianou, Yannis; Gedik, Ali Cenk; Gedik, Ali Cenk; Bozkurt, Barış
    In this paper, we suggest a novel group delay based method for the onset detection of pitched instruments. It is proposed to approach the problem of onset detection by examining three dimensions separately: phase (i.e., group delay), magnitude and pitch. The evaluation of the suggested onset detectors for phase, pitch and magnitude is performed using a new publicly available and fully onset annotated database of monophonic recordings which is balanced in terms of included instruments and onset samples per instrument, while it contains different performance styles. Results show that the accuracy of onset detection depends on the type of instruments as well as on the style of performance. Combining the information contained in the three dimensions by means of a fusion at decision level leads to an improvement of onset detection by about 8% in terms of F-measure, compared to the best single dimension. © 2010 IEEE.