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The Audio Research Group conducts research in audio content understanding, including speech, music, environmental sound, and spatial analysis. The research areas include audio classification, sound source separation, music information retrieval, sound source localization, and speech recognition, to mention a few audio analysis topics, but we study also other areas like speech synthesis. The group is composed of 15 researchers. The research topics include both basic research and more applied contract research with financing by industrial companies, TEKES, and the Finnish Academy.
Group Leader: Tuomas Virtanen
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Spectral and algebraic methods play a central role and mark a large and important field in signal processing. Broadly speaking, they comprise any harmonic analysis applied to signals of interest. We consider the synergy of abstract mathematical constructions such as function space bases, frames, function decompositions and projections, with their practical implementations through fast discrete structures.
Group Leader: Karen Egiazarian
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Interactive multimedia services will strongly influence and even dominate the future of communications and telecommunications. Both the flexibility and efficiency of the coding systems used, as well as the ability to efficiently search for particular content of interest on distributed data-bases are essential for the success of these emerging services. Since the early 1990s, content-based retrieval of digital imagery has become a very active area of research. In this context we have been developing the MUVIS, which is a system for content indexing and retrieval for mutlimedia databases.
Group Leader: Moncef Gabbouj
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Group Leader: Ioan Tabus
The main areas of research are: Genome Signal Processing, Statistical Modeling and Inference, Signal and Data Compression, and Information Theoretic Methods. The group investigations are directed both to developing new methodologies in the family of information theoretic methods and to finding new application areas where the newly derived methods could reveal their potential. The applications of data compression to full genome compressions achieved the best existing results for the human genome. A clearly tangible use of data compression in bioinformatics is to represent DNA sequences in a compact form, which is optimized for mass storage or data transmission. Additionally, the uncovering of the most effective statistical models has a profound value in understanding the patterns and interrelationships present in the biological sequence. Another highlight of the results achieved is the lossless audio compression research, where we obtain the best existing combination of compression performance and encoding/decoding speed.
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Group Leader: Irek Defée
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Group Leader: Ari Visa
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Group Leader: Alpo Värri
Biomedical signal processing is most successful when it is developed in close co-operation with physicians. The main co-operation, partner has been the Tampere University Hospital for more than ten years. In addition to domestic co-operation the laboratory has good contacts to other research groups through various EU-funded projects
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Group Leader: Ulla Ruotsalainen
The research of the group Methods and Models for Biological Signals and Images (M2oBSI) concentrates mainly on medical image reconstruction, processing and analysis. The aim is to develop automatic methods to analyze 3-D functional images. The group is working in close collaboration with the Turku PET Centre. The group is funded by the Academy of Finland, the National Technology Agency and various companies.
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Group Leader: Tapio Saramäki
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Group Leader: Olli Yli-Harja
In the Computational Systems Biology (CSB) research group, we develop and apply modeling and simulation tools for studying complex biological phenomena. The research team combines experts from different fields - cell and molecular biology, biotechnology, signal and image processing, statistics, mathematics, and computer science. We apply a systematic modeling approach to the following important areas in systems biology: quantitative simulation of underlying biological processes, quantitative modeling of modern biological measurement techniques, mathematical models for theoretical biology, and analysis, interpretation, and integration of biological data.