B
Balazs Kovesi
Researcher at Orange S.A.
Publications - 118
Citations - 987
Balazs Kovesi is an academic researcher from Orange S.A.. The author has contributed to research in topics: Signal & Audio signal. The author has an hindex of 17, co-authored 118 publications receiving 980 citations. Previous affiliations of Balazs Kovesi include Centre national d'études des télécommunications & CNET.
Papers
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Proceedings ArticleDOI
ITU-T G.729.1: AN 8-32 Kbit/S Scalable Coder Interoperable with G.729 for Wideband Telephony and Voice Over IP
Stéphane Ragot,Balazs Kovesi,Romain Trilling,David Virette,N. Duc,Dominique Massaloux,S. Proust,Bernd Geiser,Martin Gartner,Stefan Schandl,Herve Taddei,Yang Gao,E. Shlomot,Hiroyuki Ehara,K. Yoshida,Tommy Vaillancourt,R. Salami,Mi Suk Lee,Do-Young Kim +18 more
TL;DR: This paper describes the scalable coder - G.729.1 - which has been recently standardized by ITU-T for wideband telephony and voice over IP (VoIP) applications and which can operate at 12 different bit rates from 32 down to 8 kbit/s with wideband quality starting at 14 k bit/s.
Patent
Transmission error concealment in an audio signal
TL;DR: In this paper, a method of concealing transmission error in a digital audio signal in which a signal that has been decoded after transmission is received, the samples decoded while the transmitted data is valid are stored, at least one short-term prediction operator and one long-term predictive operator are estimated as a function of stored valid samples, and any missing or erroneous samples in the decoder signal are generated using the operators estimated in this way, the method being characterized in that the energy of the synthesized signal as generated in this manner is controlled by means of a gain that
Proceedings ArticleDOI
A scalable speech and audio coding scheme with continuous bitrate flexibility
TL;DR: The paper presents a novel scalable audio coding scheme where the bitrates vary continuously between a minimal and a maximal value, allowing free modification of the bitrate.
Journal ArticleDOI
Stochastic K -means algorithm for vector quantization
TL;DR: The proposed stochastic K-means algorithm (SKA) associates a vector with a cluster according to a probability distribution, which depends on the distance between the vector and the cluster gravity centre, which is less dependent on the initial centre choice than the KMA.
Patent
Dimensional vector and variable resolution quantisation
TL;DR: In this paper, an impulsion dictionary comprises: for a given dimension, increasing resolution dictionaries imbricated into each other and a union of: a totality (D'iN) of code-vectors produced, by inserting elements taken in a final set (A) into smaller dimension code vectors according to the final set of predetermined insertion rules (F1).