Imperial College London > Talks@ee.imperial > COMMSP Seminar > Adaptive Sinusoidal Models

Adaptive Sinusoidal Models

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Abstract: Sinusoidal models have been shown to be useful in various audio and speech applications like coding and modifications. In this talk I will present an extension of these models. Specifically I will present adaptive sinusoidal models, a parametric non-stationary representation of speech (and audio). Based on more sophisticate and accurate speech analysis algorithms compared to the baseline sinusoidal models, adaptive sinusoidal models offer flexibility and high quality reconstruction and modification of speech while using the same number of parameters as the baseline models. I will refer to various applications of these models in speech technologies like speech synthesis and recognition while I will make a focus on voice pathology.

Short Bio: Yannis Stylianou is Professor of Speech Processing at University of Crete, in Greece, Department of Computer Science and since 2013, he is also the Group Leader of the Speech Technology Group at Toshiba Cambridge Research Lab, UK. From 1996 until 2001 he was with AT&T Labs Research (Murray Hill and Florham Park, NJ, USA ) as a Senior Technical Staff Member. In 2001 he joined Bell-Labs Lucent Technologies, in Murray Hill, NJ, USA . He holds MSc and PhD from ENST -Paris on Signal Processing and he has studied Electrical Engineering at NTUA Athens Greece. He is an IEEE Fellow.

His current research focuses on speech signal processing algorithms for speech analysis, statistical signal processing (detection and estimation), and time-series analysis/modeling using deep learning and signal processing.

This talk is part of the COMMSP Seminar series.

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